Statement of Purpose:

I am pleased to present this case study on Frito Lay attrition, which aims to analyze and derive actionable insights from the workforce data at Frito Lay. The purpose of this study is to understand the factors influencing employee attrition, develop predictive models for attrition risk, and evaluate the performance of the predictive models.

Objectives:

  1. Data Exploration and Visualization: Conduct a thorough exploration of the available workforce data to gain insights into the distribution of various attributes.Visualize key trends and patterns related to attrition, employee demographics, and other relevant factors.
  2. Predictive Modeling: Use K-nearest neighbors (KNN) and Naive Bayes, to build predictive models for employee attrition.Evaluate the performance of each model and identify the most effective approach in predicting attrition risk. Create linear regression model to predict salary for employees, given all other predictors.
  3. Shiny App Development: Create an interactive Shiny app to visualize and communicate the insights derived from the analysis.Provide a user-friendly platform for stakeholders to explore the data and understand the implications of the findings.
  4. Communication and Collaboration: Effectively communicate the results and recommendations to stakeholders through clear and concise reports and presentations.

Load and Install Libraries

library(dplyr)
library(ggplot2)
library(caret)
library(aws.s3)
library(RCurl)
library(readr)
library(base)
library(tidyverse)
library(naniar)
library(class)
library(GGally)
library(e1071)
library(car)
library(fastDummies)

Set AWS credentials, and Load in Datasets from Amazon S3 Bucket

Here, loading in the data from the AWS S3 Bucket. I did some slight clean up of the data, to exclude the “Over18” column in the original data set and the Attrition test data set. The column name for ID in the No Salary data set was not the same, so I adjusted that. Also, I did a check for any missing values. There are no missing values in any of the data sets, so there is no need for imputing or deleting of rows.

# Load the Attrition data set from S3
#s3_path <- "s3://msds.ds.6306.2/CaseStudy2-data.csv"
# Read the Attrition Data CSV file from S3
Attritiondata <- read.table(textConnection(getURL("https://msdsds6306.s3.us-east-2.amazonaws.com/CaseStudy2-data.csv")), sep =",", header =T)
head(Attritiondata,5)
##   ID Age Attrition    BusinessTravel DailyRate             Department
## 1  1  32        No     Travel_Rarely       117                  Sales
## 2  2  40        No     Travel_Rarely      1308 Research & Development
## 3  3  35        No Travel_Frequently       200 Research & Development
## 4  4  32        No     Travel_Rarely       801                  Sales
## 5  5  24        No Travel_Frequently       567 Research & Development
##   DistanceFromHome Education   EducationField EmployeeCount EmployeeNumber
## 1               13         4    Life Sciences             1            859
## 2               14         3          Medical             1           1128
## 3               18         2    Life Sciences             1           1412
## 4                1         4        Marketing             1           2016
## 5                2         1 Technical Degree             1           1646
##   EnvironmentSatisfaction Gender HourlyRate JobInvolvement JobLevel
## 1                       2   Male         73              3        2
## 2                       3   Male         44              2        5
## 3                       3   Male         60              3        3
## 4                       3 Female         48              3        3
## 5                       1 Female         32              3        1
##                  JobRole JobSatisfaction MaritalStatus MonthlyIncome
## 1        Sales Executive               4      Divorced          4403
## 2      Research Director               3        Single         19626
## 3 Manufacturing Director               4        Single          9362
## 4        Sales Executive               4       Married         10422
## 5     Research Scientist               4        Single          3760
##   MonthlyRate NumCompaniesWorked Over18 OverTime PercentSalaryHike
## 1        9250                  2      Y       No                11
## 2       17544                  1      Y       No                14
## 3       19944                  2      Y       No                11
## 4       24032                  1      Y       No                19
## 5       17218                  1      Y      Yes                13
##   PerformanceRating RelationshipSatisfaction StandardHours StockOptionLevel
## 1                 3                        3            80                1
## 2                 3                        1            80                0
## 3                 3                        3            80                0
## 4                 3                        3            80                2
## 5                 3                        3            80                0
##   TotalWorkingYears TrainingTimesLastYear WorkLifeBalance YearsAtCompany
## 1                 8                     3               2              5
## 2                21                     2               4             20
## 3                10                     2               3              2
## 4                14                     3               3             14
## 5                 6                     2               3              6
##   YearsInCurrentRole YearsSinceLastPromotion YearsWithCurrManager
## 1                  2                       0                    3
## 2                  7                       4                    9
## 3                  2                       2                    2
## 4                 10                       5                    7
## 5                  3                       1                    3
#summary(Attritiondata)
vis_miss(Attritiondata) #checking for no missing values

#Read CSV "testing" files from S3

# Reading in of NoSalary Dataset from S3 Bucket
NoSalary<-read.table( textConnection(getURL
("https://msdsds6306.s3.us-east-2.amazonaws.com/CaseStudy2CompSet+No+Salary.csv"
)), sep=",", header=TRUE)
head(NoSalary,5)
##   ï..ID Age Attrition    BusinessTravel DailyRate             Department
## 1   871  43        No Travel_Frequently      1422                  Sales
## 2   872  33        No     Travel_Rarely       461 Research & Development
## 3   873  55       Yes     Travel_Rarely       267                  Sales
## 4   874  36        No        Non-Travel      1351 Research & Development
## 5   875  27        No     Travel_Rarely      1302 Research & Development
##   DistanceFromHome Education EducationField EmployeeCount EmployeeNumber
## 1                2         4  Life Sciences             1           1849
## 2               13         1  Life Sciences             1            995
## 3               13         4      Marketing             1           1372
## 4                9         4  Life Sciences             1           1949
## 5               19         3          Other             1           1619
##   EnvironmentSatisfaction Gender HourlyRate JobInvolvement JobLevel
## 1                       1   Male         92              3        2
## 2                       2 Female         53              3        1
## 3                       1   Male         85              4        4
## 4                       1   Male         66              4        1
## 5                       4   Male         67              2        1
##                 JobRole JobSatisfaction MaritalStatus MonthlyRate
## 1       Sales Executive               4       Married       19246
## 2    Research Scientist               4        Single       17241
## 3       Sales Executive               3        Single        9277
## 4 Laboratory Technician               2       Married        9238
## 5 Laboratory Technician               1      Divorced       16290
##   NumCompaniesWorked Over18 OverTime PercentSalaryHike PerformanceRating
## 1                  1      Y       No                20                 4
## 2                  3      Y       No                18                 3
## 3                  6      Y      Yes                17                 3
## 4                  1      Y       No                22                 4
## 5                  1      Y       No                11                 3
##   RelationshipSatisfaction StandardHours StockOptionLevel TotalWorkingYears
## 1                        3            80                1                 7
## 2                        1            80                0                 5
## 3                        3            80                0                24
## 4                        2            80                0                 5
## 5                        1            80                2                 7
##   TrainingTimesLastYear WorkLifeBalance YearsAtCompany YearsInCurrentRole
## 1                     5               3              7                  7
## 2                     4               3              3                  2
## 3                     2               2             19                  7
## 4                     3               3              5                  4
## 5                     3               3              7                  7
##   YearsSinceLastPromotion YearsWithCurrManager
## 1                       7                    7
## 2                       0                    2
## 3                       3                    8
## 4                       0                    2
## 5                       0                    7
#summary(NoSalary)
vis_miss(NoSalary)

AttritionTest<- read.table(textConnection(getURL
("https://msdsds6306.s3.us-east-2.amazonaws.com/CaseStudy2CompSet+No+Attrition.csv"
)), sep=",", header=TRUE)
head(AttritionTest,5)
##     ID Age BusinessTravel DailyRate             Department DistanceFromHome
## 1 1171  35  Travel_Rarely       750 Research & Development               28
## 2 1172  33  Travel_Rarely       147        Human Resources                2
## 3 1173  26  Travel_Rarely      1330 Research & Development               21
## 4 1174  55  Travel_Rarely      1311 Research & Development                2
## 5 1175  29  Travel_Rarely      1246                  Sales               19
##   Education  EducationField EmployeeCount EmployeeNumber
## 1         3   Life Sciences             1           1596
## 2         3 Human Resources             1           1207
## 3         3         Medical             1           1107
## 4         3   Life Sciences             1            505
## 5         3   Life Sciences             1           1497
##   EnvironmentSatisfaction Gender HourlyRate JobInvolvement JobLevel
## 1                       2   Male         46              4        2
## 2                       2   Male         99              3        1
## 3                       1   Male         37              3        1
## 4                       3 Female         97              3        4
## 5                       3   Male         77              2        2
##                 JobRole JobSatisfaction MaritalStatus MonthlyIncome MonthlyRate
## 1 Laboratory Technician               3       Married          3407       25348
## 2       Human Resources               3       Married          3600        8429
## 3 Laboratory Technician               3      Divorced          2377       19373
## 4               Manager               4        Single         16659       23258
## 5       Sales Executive               3      Divorced          8620       23757
##   NumCompaniesWorked Over18 OverTime PercentSalaryHike PerformanceRating
## 1                  1      Y       No                17                 3
## 2                  1      Y       No                13                 3
## 3                  1      Y       No                20                 4
## 4                  2      Y      Yes                13                 3
## 5                  1      Y       No                14                 3
##   RelationshipSatisfaction StandardHours StockOptionLevel TotalWorkingYears
## 1                        4            80                2                10
## 2                        4            80                1                 5
## 3                        3            80                1                 1
## 4                        3            80                0                30
## 5                        3            80                2                10
##   TrainingTimesLastYear WorkLifeBalance YearsAtCompany YearsInCurrentRole
## 1                     3               2             10                  9
## 2                     2               3              5                  4
## 3                     0               2              1                  1
## 4                     2               3              5                  4
## 5                     3               3             10                  7
##   YearsSinceLastPromotion YearsWithCurrManager
## 1                       6                    8
## 2                       1                    4
## 3                       0                    0
## 4                       1                    2
## 5                       0                    4
#summary(AttritionTest)
vis_miss(AttritionTest)

Attritiondata <- subset(Attritiondata, select = -c(Over18))
head(Attritiondata,5)
##   ID Age Attrition    BusinessTravel DailyRate             Department
## 1  1  32        No     Travel_Rarely       117                  Sales
## 2  2  40        No     Travel_Rarely      1308 Research & Development
## 3  3  35        No Travel_Frequently       200 Research & Development
## 4  4  32        No     Travel_Rarely       801                  Sales
## 5  5  24        No Travel_Frequently       567 Research & Development
##   DistanceFromHome Education   EducationField EmployeeCount EmployeeNumber
## 1               13         4    Life Sciences             1            859
## 2               14         3          Medical             1           1128
## 3               18         2    Life Sciences             1           1412
## 4                1         4        Marketing             1           2016
## 5                2         1 Technical Degree             1           1646
##   EnvironmentSatisfaction Gender HourlyRate JobInvolvement JobLevel
## 1                       2   Male         73              3        2
## 2                       3   Male         44              2        5
## 3                       3   Male         60              3        3
## 4                       3 Female         48              3        3
## 5                       1 Female         32              3        1
##                  JobRole JobSatisfaction MaritalStatus MonthlyIncome
## 1        Sales Executive               4      Divorced          4403
## 2      Research Director               3        Single         19626
## 3 Manufacturing Director               4        Single          9362
## 4        Sales Executive               4       Married         10422
## 5     Research Scientist               4        Single          3760
##   MonthlyRate NumCompaniesWorked OverTime PercentSalaryHike PerformanceRating
## 1        9250                  2       No                11                 3
## 2       17544                  1       No                14                 3
## 3       19944                  2       No                11                 3
## 4       24032                  1       No                19                 3
## 5       17218                  1      Yes                13                 3
##   RelationshipSatisfaction StandardHours StockOptionLevel TotalWorkingYears
## 1                        3            80                1                 8
## 2                        1            80                0                21
## 3                        3            80                0                10
## 4                        3            80                2                14
## 5                        3            80                0                 6
##   TrainingTimesLastYear WorkLifeBalance YearsAtCompany YearsInCurrentRole
## 1                     3               2              5                  2
## 2                     2               4             20                  7
## 3                     2               3              2                  2
## 4                     3               3             14                 10
## 5                     2               3              6                  3
##   YearsSinceLastPromotion YearsWithCurrManager
## 1                       0                    3
## 2                       4                    9
## 3                       2                    2
## 4                       5                    7
## 5                       1                    3
colnames(NoSalary)[colnames(NoSalary)=="ï..ID"] <- "ID"
colnames(NoSalary)
##  [1] "ID"                       "Age"                     
##  [3] "Attrition"                "BusinessTravel"          
##  [5] "DailyRate"                "Department"              
##  [7] "DistanceFromHome"         "Education"               
##  [9] "EducationField"           "EmployeeCount"           
## [11] "EmployeeNumber"           "EnvironmentSatisfaction" 
## [13] "Gender"                   "HourlyRate"              
## [15] "JobInvolvement"           "JobLevel"                
## [17] "JobRole"                  "JobSatisfaction"         
## [19] "MaritalStatus"            "MonthlyRate"             
## [21] "NumCompaniesWorked"       "Over18"                  
## [23] "OverTime"                 "PercentSalaryHike"       
## [25] "PerformanceRating"        "RelationshipSatisfaction"
## [27] "StandardHours"            "StockOptionLevel"        
## [29] "TotalWorkingYears"        "TrainingTimesLastYear"   
## [31] "WorkLifeBalance"          "YearsAtCompany"          
## [33] "YearsInCurrentRole"       "YearsSinceLastPromotion" 
## [35] "YearsWithCurrManager"
AttritionTest <- subset(AttritionTest, select = -c(Over18))
head(AttritionTest,5)
##     ID Age BusinessTravel DailyRate             Department DistanceFromHome
## 1 1171  35  Travel_Rarely       750 Research & Development               28
## 2 1172  33  Travel_Rarely       147        Human Resources                2
## 3 1173  26  Travel_Rarely      1330 Research & Development               21
## 4 1174  55  Travel_Rarely      1311 Research & Development                2
## 5 1175  29  Travel_Rarely      1246                  Sales               19
##   Education  EducationField EmployeeCount EmployeeNumber
## 1         3   Life Sciences             1           1596
## 2         3 Human Resources             1           1207
## 3         3         Medical             1           1107
## 4         3   Life Sciences             1            505
## 5         3   Life Sciences             1           1497
##   EnvironmentSatisfaction Gender HourlyRate JobInvolvement JobLevel
## 1                       2   Male         46              4        2
## 2                       2   Male         99              3        1
## 3                       1   Male         37              3        1
## 4                       3 Female         97              3        4
## 5                       3   Male         77              2        2
##                 JobRole JobSatisfaction MaritalStatus MonthlyIncome MonthlyRate
## 1 Laboratory Technician               3       Married          3407       25348
## 2       Human Resources               3       Married          3600        8429
## 3 Laboratory Technician               3      Divorced          2377       19373
## 4               Manager               4        Single         16659       23258
## 5       Sales Executive               3      Divorced          8620       23757
##   NumCompaniesWorked OverTime PercentSalaryHike PerformanceRating
## 1                  1       No                17                 3
## 2                  1       No                13                 3
## 3                  1       No                20                 4
## 4                  2      Yes                13                 3
## 5                  1       No                14                 3
##   RelationshipSatisfaction StandardHours StockOptionLevel TotalWorkingYears
## 1                        4            80                2                10
## 2                        4            80                1                 5
## 3                        3            80                1                 1
## 4                        3            80                0                30
## 5                        3            80                2                10
##   TrainingTimesLastYear WorkLifeBalance YearsAtCompany YearsInCurrentRole
## 1                     3               2             10                  9
## 2                     2               3              5                  4
## 3                     0               2              1                  1
## 4                     2               3              5                  4
## 5                     3               3             10                  7
##   YearsSinceLastPromotion YearsWithCurrManager
## 1                       6                    8
## 2                       1                    4
## 3                       0                    0
## 4                       1                    2
## 5                       0                    4

EDA

Looking at relationships within overall data, not just those attrited

ggplot(data=Attritiondata, aes(x=JobSatisfaction)) +geom_bar(position="dodge") + theme_minimal() + ggtitle("Overall Job Satisfaction")

Here, we look at overall Job Satisfaction among the employees. It looks like majority of employees seem to be satisfied with their job, with a handful not being as satisfied. It is a left skewed histogram.

ggplot(data=Attritiondata,aes(x=MonthlyIncome, y=Age)) + geom_point(position="jitter") + facet_wrap(~MaritalStatus)+geom_smooth(method="loess") + ggtitle("Monthly Income and Age categorized by Marital Status")

Here, we see Monthly Income by Age categorized by Marital Status. Starting off, it looks like Divorced and Married people tend to make more as their age increases. However, the same positive trend is seen for Single people, but they do not make as much as their Married or Divorced coworkers. But there is definitely a positive trend between age and monthly income.

ggplot(data = Attritiondata, aes(x = MonthlyIncome, y = Age, color = JobInvolvement)) +
  geom_point(position = "jitter") +
  geom_smooth(method = lm) +
  ggtitle("Job Involvement and Monthly Income") + facet_wrap(~JobInvolvement)

Looking at job involvement and monthly Income, it looks most employees regardless of Job Involvement have a positive correlation between Age and Monthly Income. I was trying to see if those who were more involved in their job made a higher income, but that does not seem to be the case at first glance. It looks like a lot of employees are pretty involved in their jobs (Job Involvement levels 2 and 3).

ggplot(data = Attritiondata, aes(x = MonthlyIncome, y = Age, color = interaction(JobInvolvement))) +
  geom_point(position = "jitter") +
  geom_smooth(method = lm, se = FALSE) +
  ggtitle("Job Involvement and Monthly Income")

When I plotted all 4 job levels with their respective linear regression lines, it looks like those with least job involvement (Job Involvement 1) start to make more after crossing 40 years old and a monthly income of 10,000. It seems like Job Involvement 3 make the most starting off up to a monthly income of 10,000 and ~40 years old, and start to make the least as they near 50 years old. Job Involvements 2 and 4 linear regression lines fall in between the 1 and 4 lines initially and towards the end, they are very close to each otehr, and seem to overlap.

ggplot(data=Attritiondata,aes(x=MonthlyIncome,y=NumCompaniesWorked)) + geom_point(position="jitter")  + geom_smooth(method=lm) + ggtitle("Number of Companies Worked and Monthly Income")

There is positive correlation between Monthly Income and Number of Companies worked.

ggplot(data = Attritiondata, aes(x = MonthlyIncome)) + geom_histogram()  + ggtitle("Monthly Income Histogram")

Looking at a histogram of Monthly Income, it looks to be right skewed. The mode is less than the median which is less than the mean.

ggplot(data=Attritiondata,aes(x=MonthlyIncome)) + geom_histogram() + ggtitle("Monthly Income Histogram Categorized by Gender") + facet_wrap(~Gender)

Looking at monthly income categorized by Gender, it looks like there are more male datapoints in the dataset than femalses. The mode is higher for men than it is for women. Both histograms are right skewed.

ggplot(data=Attritiondata,aes(x=MonthlyIncome, y=DistanceFromHome)) + geom_point(position="jitter") + geom_smooth(method=loess) + ggtitle("Monthly Income and Distance from Home")

There seems to be a negative correlation between distance from home and monthly income. The plot and loess curve imply that as distance from home initially increases, monthly income also increases, but after a monthly income of 15,000 is exceeded, there is an overall decrease in the distance from home. The curve resembles a concave curve, with the downward slight ‘w’ shape. Looking at this graph, I would interpret distance from home to be in miles, because if this is in kilometers, it doesn’t seem to make logical sense.

ggplot(data=Attritiondata,aes(x=MonthlyIncome, y=DistanceFromHome)) + geom_point(position="jitter") + geom_smooth(method=loess) + facet_wrap(~Gender) + ggtitle("Monthly Income and Distance from Home categorized by Gender")

There seems to be a more prominent downturned ‘w’ shape for women than for men. But the overall relationship is as mentioned above (between distance from home and Monthly Income).

ggplot(data=Attritiondata, aes(x=Department, y=JobSatisfaction, color = Gender)) + geom_point(position ="jitter") + facet_wrap(~Gender) + ggtitle("Department and Job Satisfaction by Gender")

Job Satisfaction seems to be higher for Research and Development for both Males and Females. There are less data points for those in Human Resources so a clear defined relationship can’t be concluded. There seems to be decent job satisfaction for those in Sales too for both genders.

ggplot(data=Attritiondata,aes(x=Age, y=TotalWorkingYears, color = MonthlyIncome)) + geom_point(position = "jitter") + ggtitle("Age and Total Working Years with Monthly Income")

This plot confirms that as Age increases, total working years also increase, and monthly income seems to follow the same trend as well. There is a positive correlation between all 3 variables - Age, Total working years, and monthly income.

Attrition Specific Analysis

I filtered the data to look at specifically those who Attrited, to find some insights and relationships between the variables.

attrition_yes <- dplyr::filter(Attritiondata, Attrition == "Yes")
ggplot(data = attrition_yes, aes(x = Department, fill = Gender))+ geom_bar(position = "dodge") + 
  ggtitle("Attrition by Department and Gender") + theme_minimal()

Of those who left the company, many men were in Research & Development and Sales, while there were equal amounts of women in Research & Development and Sales. There are equal amounts of men and women from Human resources who left the company.

ggplot(data = attrition_yes, aes(y = JobSatisfaction , x = DistanceFromHome, color = MonthlyIncome))+ 
geom_point(position = "jitter") + theme_minimal() + geom_smooth(method =lm) + ggtitle("Attrition by Distance from Home, Job Satisfaction with Monthly Income")

Of those who left the company, it seems likes a lot of them were making under $10,000 monthly. There seems to be a negative relationship between Job Satisfaction and Distance from home (as distance from home increases in miles, the job satisfaction goes down).

ggplot(data = attrition_yes, aes(y=JobLevel, x = MonthlyIncome, color = Age))+
  geom_point(position="jitter")+geom_smooth(method=lm) + ggtitle("Monthly Income and Job Level with Age")

Of those who left the company, there is a positive relationship between job level and Monthly income. Age seems to be scattered, but at a job level of around 1, and monthly income less than 5000, the age group seems to have employees in their 20s.

ggplot(data = attrition_yes, aes(y=JobLevel, x = Age, color = Gender))+
  geom_point(position="jitter")+geom_smooth(method=lm) + ggtitle("Attrition Job Level by Age and Gender")

OF those who left the company, it looks like Job Level is positively correlated with Age for both Males and Females. The slope of the linear regression line for females seems to be more steep than it is for the males.

ggplot(data = attrition_yes, aes(x=OverTime, fill = Gender)) + geom_bar() + ggtitle("Attrition -  Overtime by Gender")

Of those who left the company, many employees were working over time. As mentioned earlier, there are more male data points compared to females, which is why at first glance it may seem a bit off. It looks like of the Over time group - approximately 70% were males, and 30% was females.

ggplot(data = attrition_yes, aes(x=NumCompaniesWorked, y = PercentSalaryHike)) + geom_point(position = "jitter") + theme_minimal()+geom_smooth(method = lm) + ggtitle ("Attrition - Percent Salary Hike and Number of Companies Worked")

There seems to be a slight downward trend when looking at the relationship between Number of companies worked and Percent salary hike. I was trying to see if the number of companies worked affected the percent salary hike positively. At first glance, it seems like there is no variation int he line, but if you observe closely, there is a slight downward trend.

ggplot(data = attrition_yes, aes(x = PercentSalaryHike, fill = OverTime)) +
  geom_histogram( binwidth = 1, color = "black", alpha = 0.7) +
  geom_density(aes(y = ..count..), fill = "transparent", color = "darkblue") +
  labs(title = "Histogram with Trend Line of % Salary Hike by Overtime",
       x = "Percent Salary Hike", y = "Count") +
  theme_minimal() + theme(legend.position = "top")  # Adjust legend position

This is a histogram of percent salary hike, with each bar being split and shaded by if the employee(s) were working over time. The overall percent salary hike (without the split) seems to be right skewed generally, but the shape of the line/trend seems to imply that it may be multimodal.

ggplot(data = attrition_yes, aes(x=YearsAtCompany, y = PercentSalaryHike, color = PerformanceRating)) + geom_point() + theme_minimal() + ggtitle("Salary Hike v. Years at Company with Performance Rating")

This plot takes a look at Years at Company and Percent salary hike. Those with a higher performance rating seem to have a higher percent salary hike. For a Percent salary hike less than 20%, it seems like the performance rating is under 4, and trends around the 3 rating.

ggplot(data = attrition_yes, aes(y=JobSatisfaction, x = Education)) + geom_point(position="jitter") + theme_minimal() + ggtitle("Job Satisfaction v. Education Categorized by Education Field") + facet_wrap(~EducationField) + geom_smooth(method = lm)

This plot looks at the relationship between Job Satisfaction based on Education categorized by education field. Most education fields seem to have a negative correlation between job satisfaction and years of education, except for the Medical field. The medical field is the only field where as education increases, the job satifaction also seems to increase.

#Building a Regression Model to Determine Salary

Regression Model 1 Using All Predictors to Determine Salary

Monthly Income is the “salary” variable

class(Attritiondata$MonthlyIncome)
## [1] "integer"
sum(is.na(Attritiondata$MonthlyIncome))
## [1] 0
summary(Attritiondata)
##        ID             Age         Attrition         BusinessTravel    
##  Min.   :  1.0   Min.   :18.00   Length:870         Length:870        
##  1st Qu.:218.2   1st Qu.:30.00   Class :character   Class :character  
##  Median :435.5   Median :35.00   Mode  :character   Mode  :character  
##  Mean   :435.5   Mean   :36.83                                        
##  3rd Qu.:652.8   3rd Qu.:43.00                                        
##  Max.   :870.0   Max.   :60.00                                        
##    DailyRate       Department        DistanceFromHome   Education    
##  Min.   : 103.0   Length:870         Min.   : 1.000   Min.   :1.000  
##  1st Qu.: 472.5   Class :character   1st Qu.: 2.000   1st Qu.:2.000  
##  Median : 817.5   Mode  :character   Median : 7.000   Median :3.000  
##  Mean   : 815.2                      Mean   : 9.339   Mean   :2.901  
##  3rd Qu.:1165.8                      3rd Qu.:14.000   3rd Qu.:4.000  
##  Max.   :1499.0                      Max.   :29.000   Max.   :5.000  
##  EducationField     EmployeeCount EmployeeNumber   EnvironmentSatisfaction
##  Length:870         Min.   :1     Min.   :   1.0   Min.   :1.000          
##  Class :character   1st Qu.:1     1st Qu.: 477.2   1st Qu.:2.000          
##  Mode  :character   Median :1     Median :1039.0   Median :3.000          
##                     Mean   :1     Mean   :1029.8   Mean   :2.701          
##                     3rd Qu.:1     3rd Qu.:1561.5   3rd Qu.:4.000          
##                     Max.   :1     Max.   :2064.0   Max.   :4.000          
##     Gender            HourlyRate     JobInvolvement     JobLevel    
##  Length:870         Min.   : 30.00   Min.   :1.000   Min.   :1.000  
##  Class :character   1st Qu.: 48.00   1st Qu.:2.000   1st Qu.:1.000  
##  Mode  :character   Median : 66.00   Median :3.000   Median :2.000  
##                     Mean   : 65.61   Mean   :2.723   Mean   :2.039  
##                     3rd Qu.: 83.00   3rd Qu.:3.000   3rd Qu.:3.000  
##                     Max.   :100.00   Max.   :4.000   Max.   :5.000  
##    JobRole          JobSatisfaction MaritalStatus      MonthlyIncome  
##  Length:870         Min.   :1.000   Length:870         Min.   : 1081  
##  Class :character   1st Qu.:2.000   Class :character   1st Qu.: 2840  
##  Mode  :character   Median :3.000   Mode  :character   Median : 4946  
##                     Mean   :2.709                      Mean   : 6390  
##                     3rd Qu.:4.000                      3rd Qu.: 8182  
##                     Max.   :4.000                      Max.   :19999  
##   MonthlyRate    NumCompaniesWorked   OverTime         PercentSalaryHike
##  Min.   : 2094   Min.   :0.000      Length:870         Min.   :11.0     
##  1st Qu.: 8092   1st Qu.:1.000      Class :character   1st Qu.:12.0     
##  Median :14074   Median :2.000      Mode  :character   Median :14.0     
##  Mean   :14326   Mean   :2.728                         Mean   :15.2     
##  3rd Qu.:20456   3rd Qu.:4.000                         3rd Qu.:18.0     
##  Max.   :26997   Max.   :9.000                         Max.   :25.0     
##  PerformanceRating RelationshipSatisfaction StandardHours StockOptionLevel
##  Min.   :3.000     Min.   :1.000            Min.   :80    Min.   :0.0000  
##  1st Qu.:3.000     1st Qu.:2.000            1st Qu.:80    1st Qu.:0.0000  
##  Median :3.000     Median :3.000            Median :80    Median :1.0000  
##  Mean   :3.152     Mean   :2.707            Mean   :80    Mean   :0.7839  
##  3rd Qu.:3.000     3rd Qu.:4.000            3rd Qu.:80    3rd Qu.:1.0000  
##  Max.   :4.000     Max.   :4.000            Max.   :80    Max.   :3.0000  
##  TotalWorkingYears TrainingTimesLastYear WorkLifeBalance YearsAtCompany  
##  Min.   : 0.00     Min.   :0.000         Min.   :1.000   Min.   : 0.000  
##  1st Qu.: 6.00     1st Qu.:2.000         1st Qu.:2.000   1st Qu.: 3.000  
##  Median :10.00     Median :3.000         Median :3.000   Median : 5.000  
##  Mean   :11.05     Mean   :2.832         Mean   :2.782   Mean   : 6.962  
##  3rd Qu.:15.00     3rd Qu.:3.000         3rd Qu.:3.000   3rd Qu.:10.000  
##  Max.   :40.00     Max.   :6.000         Max.   :4.000   Max.   :40.000  
##  YearsInCurrentRole YearsSinceLastPromotion YearsWithCurrManager
##  Min.   : 0.000     Min.   : 0.000          Min.   : 0.00       
##  1st Qu.: 2.000     1st Qu.: 0.000          1st Qu.: 2.00       
##  Median : 3.000     Median : 1.000          Median : 3.00       
##  Mean   : 4.205     Mean   : 2.169          Mean   : 4.14       
##  3rd Qu.: 7.000     3rd Qu.: 3.000          3rd Qu.: 7.00       
##  Max.   :18.000     Max.   :15.000          Max.   :17.00
# Identify character variables
char_vars <- sapply(Attritiondata, is.character)
# Convert character variables to factors
Attritiondata[, char_vars] <- lapply(Attritiondata[, char_vars], as.factor)

#Check Factor Levels for Categorical variables:
sapply(Attritiondata[,char_vars],levels)
## $Attrition
## [1] "No"  "Yes"
## 
## $BusinessTravel
## [1] "Non-Travel"        "Travel_Frequently" "Travel_Rarely"    
## 
## $Department
## [1] "Human Resources"        "Research & Development" "Sales"                 
## 
## $EducationField
## [1] "Human Resources"  "Life Sciences"    "Marketing"        "Medical"         
## [5] "Other"            "Technical Degree"
## 
## $Gender
## [1] "Female" "Male"  
## 
## $JobRole
## [1] "Healthcare Representative" "Human Resources"          
## [3] "Laboratory Technician"     "Manager"                  
## [5] "Manufacturing Director"    "Research Director"        
## [7] "Research Scientist"        "Sales Executive"          
## [9] "Sales Representative"     
## 
## $MaritalStatus
## [1] "Divorced" "Married"  "Single"  
## 
## $OverTime
## [1] "No"  "Yes"
  #Noticed Over18 has only 1 factor level; so going to remove from dataset
 # Attritiondata <- subset(Attritiondata, select = -c(Over18))

# Fit the linear regression model with all predictors
Model1_fit <- lm(MonthlyIncome ~ ., data = Attritiondata)
summary(Model1_fit)
## 
## Call:
## lm(formula = MonthlyIncome ~ ., data = Attritiondata)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -3708.8  -674.1    14.7   614.1  4100.0 
## 
## Coefficients: (2 not defined because of singularities)
##                                    Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                       6.013e+01  7.772e+02   0.077 0.938349    
## ID                               -2.343e-01  1.476e-01  -1.588 0.112713    
## Age                              -1.431e+00  5.649e+00  -0.253 0.800110    
## AttritionYes                      8.904e+01  1.154e+02   0.771 0.440729    
## BusinessTravelTravel_Frequently   1.895e+02  1.420e+02   1.334 0.182441    
## BusinessTravelTravel_Rarely       3.720e+02  1.200e+02   3.099 0.002005 ** 
## DailyRate                         1.452e-01  9.129e-02   1.591 0.112062    
## DepartmentResearch & Development  1.234e+02  4.768e+02   0.259 0.795866    
## DepartmentSales                  -4.594e+02  4.877e+02  -0.942 0.346580    
## DistanceFromHome                 -6.237e+00  4.578e+00  -1.362 0.173417    
## Education                        -3.743e+01  3.716e+01  -1.007 0.314105    
## EducationFieldLife Sciences       1.352e+02  3.692e+02   0.366 0.714248    
## EducationFieldMarketing           1.377e+02  3.914e+02   0.352 0.725050    
## EducationFieldMedical             3.326e+01  3.699e+02   0.090 0.928376    
## EducationFieldOther               9.152e+01  3.946e+02   0.232 0.816664    
## EducationFieldTechnical Degree    9.680e+01  3.843e+02   0.252 0.801179    
## EmployeeCount                            NA         NA      NA       NA    
## EmployeeNumber                    8.681e-02  6.103e-02   1.422 0.155269    
## EnvironmentSatisfaction          -6.267e+00  3.364e+01  -0.186 0.852252    
## GenderMale                        1.100e+02  7.442e+01   1.478 0.139715    
## HourlyRate                       -3.591e-01  1.824e+00  -0.197 0.844003    
## JobInvolvement                    1.677e+01  5.321e+01   0.315 0.752698    
## JobLevel                          2.783e+03  8.340e+01  33.375  < 2e-16 ***
## JobRoleHuman Resources           -2.053e+02  5.157e+02  -0.398 0.690663    
## JobRoleLaboratory Technician     -5.891e+02  1.714e+02  -3.437 0.000618 ***
## JobRoleManager                    4.280e+03  2.830e+02  15.122  < 2e-16 ***
## JobRoleManufacturing Director     1.809e+02  1.696e+02   1.067 0.286497    
## JobRoleResearch Director          4.077e+03  2.193e+02  18.592  < 2e-16 ***
## JobRoleResearch Scientist        -3.494e+02  1.705e+02  -2.049 0.040790 *  
## JobRoleSales Executive            5.263e+02  3.576e+02   1.472 0.141449    
## JobRoleSales Representative       8.531e+01  3.918e+02   0.218 0.827703    
## JobSatisfaction                   3.278e+01  3.344e+01   0.980 0.327278    
## MaritalStatusMarried              6.708e+01  1.002e+02   0.669 0.503497    
## MaritalStatusSingle               1.128e+01  1.361e+02   0.083 0.933978    
## MonthlyRate                      -9.505e-03  5.143e-03  -1.848 0.064946 .  
## NumCompaniesWorked                5.421e+00  1.691e+01   0.321 0.748622    
## OverTimeYes                      -1.394e+01  8.434e+01  -0.165 0.868787    
## PercentSalaryHike                 2.586e+01  1.581e+01   1.635 0.102351    
## PerformanceRating                -3.235e+02  1.614e+02  -2.004 0.045368 *  
## RelationshipSatisfaction          1.640e+01  3.339e+01   0.491 0.623375    
## StandardHours                            NA         NA      NA       NA    
## StockOptionLevel                 -2.758e+00  5.740e+01  -0.048 0.961695    
## TotalWorkingYears                 5.080e+01  1.098e+01   4.627  4.3e-06 ***
## TrainingTimesLastYear             2.436e+01  2.912e+01   0.837 0.403111    
## WorkLifeBalance                  -3.472e+01  5.161e+01  -0.673 0.501284    
## YearsAtCompany                   -2.750e+00  1.370e+01  -0.201 0.840925    
## YearsInCurrentRole                3.398e+00  1.711e+01   0.199 0.842584    
## YearsSinceLastPromotion           3.084e+01  1.532e+01   2.013 0.044405 *  
## YearsWithCurrManager             -2.691e+01  1.669e+01  -1.613 0.107210    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1055 on 823 degrees of freedom
## Multiple R-squared:  0.9501, Adjusted R-squared:  0.9473 
## F-statistic: 340.7 on 46 and 823 DF,  p-value: < 2.2e-16
#p val < alpha of .05, it affects the Salary Variable

#Model1_Preds = predict(Model1_fit, newdata = NoSalary) #this is an example of predict function you would want to use
#as.data.frame(Model1_Preds)
#write.csv(Model1_Preds,"Model1PredictionsNoSalaryRenuKarthikeyan.csv")

Looking at this summary of model 1 output, it indicates that the statistically significant p values are Business Travel, JobLevel, Job Role, Performance rating, Total working Years, and Years since last promotion. The F-statistic tests the overall significance of the model. The F-statistic is 340.7 with a very small p-value (< 2.2e-16), suggests that at least one predictor variable is significantly related to Monthly Income.There are two coefficients not defined because of singularities. This might indicate multicollinearity, where two or more predictor variables are highly correlated.

Linear Regression using Select predictors to Determine Salary

Model2_fit = lm(MonthlyIncome ~ NumCompaniesWorked + Age + Gender + MaritalStatus + JobInvolvement + JobRole + DistanceFromHome + JobLevel + Education, data = Attritiondata)
summary(Model2_fit) # P value overall implies that at least one of my variables' slope != 0. 
## 
## Call:
## lm(formula = MonthlyIncome ~ NumCompaniesWorked + Age + Gender + 
##     MaritalStatus + JobInvolvement + JobRole + DistanceFromHome + 
##     JobLevel + Education, data = Attritiondata)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -3536.4  -699.4   -39.1   659.8  4178.5 
## 
## Coefficients:
##                               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                   -600.926    320.383  -1.876  0.06105 .  
## NumCompaniesWorked              17.866     15.366   1.163  0.24526    
## Age                             12.875      4.962   2.595  0.00963 ** 
## GenderMale                     120.277     75.308   1.597  0.11061    
## MaritalStatusMarried           106.159     95.406   1.113  0.26615    
## MaritalStatusSingle             23.451    103.944   0.226  0.82155    
## JobInvolvement                  15.469     52.613   0.294  0.76882    
## JobRoleHuman Resources        -327.849    255.950  -1.281  0.20057    
## JobRoleLaboratory Technician  -534.026    172.285  -3.100  0.00200 ** 
## JobRoleManager                3933.510    232.847  16.893  < 2e-16 ***
## JobRoleManufacturing Director   92.825    169.877   0.546  0.58492    
## JobRoleResearch Director      3919.755    218.518  17.938  < 2e-16 ***
## JobRoleResearch Scientist     -246.097    171.976  -1.431  0.15280    
## JobRoleSales Executive        -122.894    146.575  -0.838  0.40202    
## JobRoleSales Representative   -392.881    217.075  -1.810  0.07067 .  
## DistanceFromHome                -7.908      4.553  -1.737  0.08281 .  
## JobLevel                      3042.789     69.854  43.559  < 2e-16 ***
## Education                      -33.713     37.379  -0.902  0.36736    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1078 on 852 degrees of freedom
## Multiple R-squared:  0.9461, Adjusted R-squared:  0.945 
## F-statistic: 878.9 on 17 and 852 DF,  p-value: < 2.2e-16
NoSalary$MonthlyIncome = predict(Model2_fit,newdata = NoSalary)

#Model2_Preds<- NoSalary %>% select(c("ID","MonthlyIncome"))
#as.data.frame(Model2_Preds)
#write.csv(Model2_Preds,"Model2PredictionsNoSalaryRenuKarthikeyan.csv", row.names = T)

These select predictors were chosen because of the insights from the EDA. I thought they were significant predictors. The coefficient for JobLevel is 3042.789. This suggests that, on average, an increase of one unit in JobLevel is associated with an increase of 3042.789 dollars in MonthlyIncome.Likewise, Age has a coefficient of 12.875 indicating that a year increase in age, results in 12.88 dollars additional monthly income, holding all other variables constant. Males have a coefficient of 120, indicating that holding all other variables constant, males make an additional 120 dollars compared to women monthly. The coefficient for distance from home has a. -7.908, which indicates each additional mile away from home may result in a monthly salary decrease by -7 dollars.

The statistically significant p values (<.10) are Age, certain Job Roles – like Laboratory Technician, Manager, and Research director, Job Level;

Overall, Model 2 appears to have a high R-squared value, indicating a good fit to the data. Many predictors are statistically significant, suggesting they contribute to determining Monthly Income

Split and Train Linear Regression Models to Predict Salary, with average of cross validation

set.seed(1234)
TrainObs = sample(seq(1,dim(Attritiondata)[1]),round(.8*dim(Attritiondata)[1]),replace = FALSE)
SalaryTrain = Attritiondata[TrainObs,]
SalaryTrain
##      ID Age Attrition    BusinessTravel DailyRate             Department
## 284 284  31        No     Travel_Rarely       691                  Sales
## 848 848  39        No     Travel_Rarely      1132 Research & Development
## 101 101  27        No     Travel_Rarely      1377 Research & Development
## 623 623  34        No     Travel_Rarely       182 Research & Development
## 645 645  41       Yes        Non-Travel       906 Research & Development
## 400 400  44        No Travel_Frequently      1193 Research & Development
## 98   98  37        No        Non-Travel      1040 Research & Development
## 103 103  34        No        Non-Travel      1381                  Sales
## 726 726  25        No     Travel_Rarely       685 Research & Development
## 602 602  32        No        Non-Travel      1200 Research & Development
## 326 326  27        No     Travel_Rarely       618 Research & Development
## 79   79  45        No        Non-Travel      1052                  Sales
## 270 270  30        No     Travel_Rarely      1176 Research & Development
## 382 382  26        No     Travel_Rarely      1355        Human Resources
## 184 184  39        No     Travel_Rarely      1089 Research & Development
## 574 574  34        No     Travel_Rarely       810                  Sales
## 4     4  32        No     Travel_Rarely       801                  Sales
## 661 661  32        No Travel_Frequently       430 Research & Development
## 552 552  28        No     Travel_Rarely      1169        Human Resources
## 212 212  42        No     Travel_Rarely       265                  Sales
## 195 195  26        No     Travel_Rarely       683 Research & Development
## 511 511  38        No     Travel_Rarely       345                  Sales
## 479 479  52        No     Travel_Rarely       258 Research & Development
## 605 605  29       Yes     Travel_Rarely       428                  Sales
## 634 634  36        No     Travel_Rarely       922 Research & Development
## 578 578  44        No        Non-Travel       981 Research & Development
## 510 510  41       Yes     Travel_Rarely      1360 Research & Development
## 687 687  29       Yes Travel_Frequently       337 Research & Development
## 424 424  18        No        Non-Travel      1124 Research & Development
## 379 379  29        No     Travel_Rarely       942 Research & Development
## 816 816  33        No     Travel_Rarely       117 Research & Development
## 108 108  55        No     Travel_Rarely       189        Human Resources
## 131 131  29        No     Travel_Rarely       991                  Sales
## 343 343  33        No     Travel_Rarely       654 Research & Development
## 41   41  58        No        Non-Travel       350                  Sales
## 627 627  24        No     Travel_Rarely      1476                  Sales
## 740 740  35        No     Travel_Rarely       538 Research & Development
## 298 298  34       Yes Travel_Frequently       658 Research & Development
## 811 811  30        No        Non-Travel       111 Research & Development
## 258 258  30        No     Travel_Rarely       855                  Sales
## 629 629  55        No Travel_Frequently      1091 Research & Development
## 859 859  41        No     Travel_Rarely       933 Research & Development
## 182 182  38        No     Travel_Rarely      1009                  Sales
## 305 305  58       Yes     Travel_Rarely       289 Research & Development
## 358 358  29       Yes     Travel_Rarely       408 Research & Development
## 696 696  47        No     Travel_Rarely      1454                  Sales
## 307 307  50        No     Travel_Rarely       804 Research & Development
## 827 827  31       Yes     Travel_Rarely      1079                  Sales
## 221 221  34        No     Travel_Rarely       304                  Sales
## 736 736  27        No     Travel_Rarely       511                  Sales
## 561 561  36        No Travel_Frequently      1480 Research & Development
## 313 313  31       Yes Travel_Frequently       561 Research & Development
## 136 136  40        No Travel_Frequently       791 Research & Development
## 794 794  36        No     Travel_Rarely      1223 Research & Development
## 145 145  40        No     Travel_Rarely      1202 Research & Development
## 123 123  45        No     Travel_Rarely       930                  Sales
## 776 776  23        No     Travel_Rarely       310 Research & Development
## 234 234  54        No     Travel_Rarely      1147                  Sales
## 608 608  38        No     Travel_Rarely       322                  Sales
## 495 495  36        No     Travel_Rarely      1266                  Sales
## 534 534  32        No        Non-Travel      1146 Research & Development
## 803 803  39        No     Travel_Rarely       117 Research & Development
## 297 297  34        No Travel_Frequently      1069 Research & Development
## 208 208  38       Yes     Travel_Rarely      1180 Research & Development
## 838 838  34        No     Travel_Rarely       258                  Sales
## 569 569  42        No     Travel_Rarely       462                  Sales
## 522 522  28       Yes     Travel_Rarely       329 Research & Development
## 248 248  32        No     Travel_Rarely       234                  Sales
## 365 365  55        No     Travel_Rarely       282 Research & Development
## 665 665  34        No        Non-Travel      1065                  Sales
## 643 643  55        No        Non-Travel       444 Research & Development
## 595 595  40        No     Travel_Rarely       884 Research & Development
## 434 434  29        No     Travel_Rarely       590 Research & Development
## 757 757  35        No     Travel_Rarely      1137 Research & Development
## 760 760  45       Yes     Travel_Rarely      1449                  Sales
## 218 218  48        No Travel_Frequently       117 Research & Development
## 727 727  37        No Travel_Frequently      1231                  Sales
## 508 508  51        No Travel_Frequently       541                  Sales
## 276 276  56        No     Travel_Rarely       718 Research & Development
## 169 169  52        No     Travel_Rarely       956 Research & Development
## 71   71  41        No     Travel_Rarely       642 Research & Development
## 573 573  28        No Travel_Frequently       783                  Sales
## 860 860  44       Yes     Travel_Rarely       621 Research & Development
## 485 485  58       Yes     Travel_Rarely       147 Research & Development
## 667 667  29        No Travel_Frequently      1413                  Sales
## 460 460  36        No     Travel_Rarely       172 Research & Development
## 60   60  25       Yes Travel_Frequently       599                  Sales
## 449 449  38        No Travel_Frequently       653 Research & Development
## 548 548  40        No Travel_Frequently       720 Research & Development
## 19   19  34        No     Travel_Rarely       181 Research & Development
## 649 649  35        No     Travel_Rarely       776                  Sales
## 638 638  34        No     Travel_Rarely      1239                  Sales
## 670 670  54        No     Travel_Rarely       685 Research & Development
## 319 319  39        No     Travel_Rarely      1498                  Sales
## 116 116  37        No        Non-Travel      1252                  Sales
## 840 840  48        No     Travel_Rarely      1224 Research & Development
## 102 102  31        No     Travel_Rarely       326                  Sales
## 214 214  42        No     Travel_Rarely       932 Research & Development
## 390 390  21       Yes Travel_Frequently       756                  Sales
## 597 597  35        No     Travel_Rarely       672 Research & Development
## 771 771  33        No Travel_Frequently       508                  Sales
## 160 160  42        No Travel_Frequently       458 Research & Development
## 77   77  34        No     Travel_Rarely       971                  Sales
## 529 529  35        No     Travel_Rarely      1214 Research & Development
## 126 126  35        No     Travel_Rarely      1224                  Sales
## 262 262  29       Yes     Travel_Rarely       224 Research & Development
## 442 442  29        No     Travel_Rarely      1082 Research & Development
## 642 642  40        No     Travel_Rarely       750 Research & Development
## 181 181  35        No     Travel_Rarely       819 Research & Development
## 163 163  33        No     Travel_Rarely      1216                  Sales
## 474 474  45        No     Travel_Rarely      1316 Research & Development
## 228 228  22        No     Travel_Rarely      1136 Research & Development
## 774 774  36       Yes     Travel_Rarely       318 Research & Development
## 646 646  40        No     Travel_Rarely       630                  Sales
## 265 265  24        No     Travel_Rarely      1127 Research & Development
## 427 427  30        No        Non-Travel       990 Research & Development
## 781 781  41       Yes     Travel_Rarely      1356                  Sales
## 249 249  41        No Travel_Frequently      1200 Research & Development
## 810 810  27        No     Travel_Rarely      1157 Research & Development
## 40   40  31        No Travel_Frequently       793                  Sales
## 541 541  30        No     Travel_Rarely       853 Research & Development
## 497 497  45        No     Travel_Rarely       192 Research & Development
## 697 697  48        No Travel_Frequently       365 Research & Development
## 865 865  45        No     Travel_Rarely      1448 Research & Development
## 450 450  45        No        Non-Travel       336                  Sales
## 600 600  24       Yes     Travel_Rarely       813 Research & Development
## 778 778  32        No        Non-Travel       862                  Sales
## 363 363  52       Yes     Travel_Rarely       266                  Sales
## 478 478  26        No     Travel_Rarely       775                  Sales
## 403 403  47        No     Travel_Rarely       207 Research & Development
## 375 375  20        No     Travel_Rarely       727                  Sales
## 335 335  59        No        Non-Travel      1420        Human Resources
## 598 598  40        No     Travel_Rarely       555 Research & Development
## 142 142  58        No     Travel_Rarely       848 Research & Development
## 444 444  44        No     Travel_Rarely       528        Human Resources
## 741 741  25        No     Travel_Rarely       959                  Sales
## 659 659  41        No     Travel_Rarely       483 Research & Development
## 790 790  25        No     Travel_Rarely       266 Research & Development
## 457 457  31        No     Travel_Rarely      1112                  Sales
## 188 188  47        No     Travel_Rarely      1225                  Sales
## 432 432  40        No        Non-Travel       458 Research & Development
## 488 488  31        No     Travel_Rarely       670 Research & Development
## 538 538  42        No     Travel_Rarely       544        Human Resources
## 752 752  31       Yes Travel_Frequently      1060                  Sales
## 215 215  27        No     Travel_Rarely      1115 Research & Development
## 540 540  42        No     Travel_Rarely       647                  Sales
## 613 613  33       Yes     Travel_Rarely       465 Research & Development
## 730 730  22        No     Travel_Rarely       594 Research & Development
## 296 296  35        No     Travel_Rarely      1490 Research & Development
## 328 328  42        No     Travel_Rarely       557 Research & Development
## 147 147  33        No     Travel_Rarely       931 Research & Development
## 701 701  29        No     Travel_Rarely       352        Human Resources
## 708 708  31        No     Travel_Rarely      1398        Human Resources
## 84   84  37        No     Travel_Rarely      1319 Research & Development
## 83   83  38        No Travel_Frequently       508 Research & Development
## 250 250  41        No     Travel_Rarely      1276                  Sales
## 767 767  41        No     Travel_Rarely       509 Research & Development
## 281 281  43        No     Travel_Rarely      1179                  Sales
## 675 675  27        No     Travel_Rarely       486 Research & Development
## 843 843  52        No Travel_Frequently       890 Research & Development
## 431 431  27        No     Travel_Rarely      1377                  Sales
## 30   30  52        No        Non-Travel       715 Research & Development
## 10   10  34        No Travel_Frequently       653 Research & Development
## 817 817  30        No     Travel_Rarely       946 Research & Development
## 441 441  32        No Travel_Frequently      1316 Research & Development
## 820 820  28       Yes     Travel_Rarely      1475                  Sales
## 345 345  30        No     Travel_Rarely      1329                  Sales
## 592 592  34       Yes     Travel_Rarely       790                  Sales
## 585 585  44        No     Travel_Rarely      1459 Research & Development
## 660 660  36        No Travel_Frequently      1195 Research & Development
## 12   12  28        No        Non-Travel       280        Human Resources
## 293 293  27        No     Travel_Rarely       894 Research & Development
## 303 303  55        No     Travel_Rarely      1441 Research & Development
## 738 738  59        No     Travel_Rarely       326                  Sales
## 678 678  40        No Travel_Frequently       692 Research & Development
## 338 338  34        No Travel_Frequently       618 Research & Development
## 350 350  56        No     Travel_Rarely       832 Research & Development
## 720 720  28        No     Travel_Rarely       950 Research & Development
## 658 658  54        No Travel_Frequently      1050 Research & Development
## 107 107  29        No        Non-Travel      1496 Research & Development
## 543 543  27        No        Non-Travel      1450 Research & Development
## 518 518  42        No     Travel_Rarely       855 Research & Development
## 854 854  28        No     Travel_Rarely      1476 Research & Development
## 43   43  49        No     Travel_Rarely       464 Research & Development
## 189 189  50        No     Travel_Rarely       797 Research & Development
## 171 171  30        No     Travel_Rarely       501                  Sales
## 39   39  56        No     Travel_Rarely       206        Human Resources
## 216 216  40        No     Travel_Rarely       896 Research & Development
## 291 291  45        No     Travel_Rarely       974 Research & Development
## 58   58  29        No     Travel_Rarely      1370 Research & Development
## 395 395  42        No Travel_Frequently      1271 Research & Development
## 856 856  35        No     Travel_Rarely       660                  Sales
## 456 456  40        No     Travel_Rarely       611                  Sales
## 22   22  48        No     Travel_Rarely       817                  Sales
## 170 170  29        No     Travel_Rarely      1107 Research & Development
## 588 588  36       Yes     Travel_Rarely      1218                  Sales
## 63   63  31        No     Travel_Rarely      1154                  Sales
## 676 676  46        No     Travel_Rarely       168                  Sales
## 719 719  35       Yes Travel_Frequently       880                  Sales
## 417 417  30        No        Non-Travel      1116 Research & Development
## 789 789  55        No     Travel_Rarely       478 Research & Development
## 70   70  37        No     Travel_Rarely      1372 Research & Development
## 59   59  37        No        Non-Travel       728 Research & Development
## 800 800  36        No     Travel_Rarely      1040 Research & Development
## 484 484  56        No     Travel_Rarely       713 Research & Development
## 203 203  32        No     Travel_Rarely       859 Research & Development
## 227 227  35        No     Travel_Rarely       464 Research & Development
## 243 243  29        No     Travel_Rarely      1328 Research & Development
## 413 413  37        No     Travel_Rarely       408 Research & Development
## 577 577  38        No     Travel_Rarely      1404                  Sales
## 542 542  33        No     Travel_Rarely       867 Research & Development
## 476 476  46        No Travel_Frequently      1211                  Sales
## 744 744  23        No     Travel_Rarely       160 Research & Development
## 804 804  35       Yes     Travel_Rarely      1204                  Sales
## 405 405  35        No     Travel_Rarely      1343 Research & Development
## 397 397  46        No     Travel_Rarely      1009 Research & Development
## 607 607  59        No Travel_Frequently      1225                  Sales
## 501 501  58       Yes     Travel_Rarely       601 Research & Development
## 429 429  32       Yes     Travel_Rarely       515 Research & Development
## 205 205  32        No     Travel_Rarely      1401                  Sales
## 475 475  28        No     Travel_Rarely       895 Research & Development
## 104 104  23        No     Travel_Rarely       885 Research & Development
## 210 210  41        No     Travel_Rarely       802                  Sales
## 471 471  27        No     Travel_Rarely      1354 Research & Development
## 66   66  32        No     Travel_Rarely       334 Research & Development
## 88   88  35       Yes     Travel_Rarely       622 Research & Development
## 826 826  46        No     Travel_Rarely       430 Research & Development
## 601 601  24        No        Non-Travel       830                  Sales
## 309 309  55        No Travel_Frequently       135 Research & Development
## 737 737  39        No     Travel_Rarely       722                  Sales
## 294 294  47        No        Non-Travel      1162 Research & Development
## 421 421  34        No     Travel_Rarely      1153 Research & Development
## 769 769  46        No     Travel_Rarely       150 Research & Development
## 430 430  34        No     Travel_Rarely       470 Research & Development
## 512 512  39        No        Non-Travel      1485 Research & Development
## 361 361  52        No     Travel_Rarely       699 Research & Development
## 814 814  47        No     Travel_Rarely      1176        Human Resources
## 480 480  37        No     Travel_Rarely       161 Research & Development
## 15   15  46        No     Travel_Rarely       991        Human Resources
## 486 486  41       Yes     Travel_Rarely      1102                  Sales
## 254 254  31       Yes     Travel_Rarely       359        Human Resources
## 491 491  49        No Travel_Frequently       636 Research & Development
## 713 713  48        No     Travel_Rarely       969 Research & Development
## 178 178  26       Yes Travel_Frequently       342 Research & Development
## 428 428  21        No     Travel_Rarely       996 Research & Development
## 691 691  38        No Travel_Frequently       888        Human Resources
## 194 194  48        No     Travel_Rarely       163                  Sales
## 599 599  27        No     Travel_Rarely       155 Research & Development
## 802 802  31        No     Travel_Rarely       828                  Sales
## 378 378  42        No     Travel_Rarely       419                  Sales
## 639 639  24        No     Travel_Rarely       691 Research & Development
## 155 155  34        No     Travel_Rarely       546 Research & Development
## 166 166  20       Yes     Travel_Rarely       500                  Sales
## 207 207  43       Yes     Travel_Rarely      1372                  Sales
## 468 468  36        No     Travel_Rarely       132 Research & Development
## 105 105  53        No     Travel_Rarely       447 Research & Development
## 482 482  31        No     Travel_Rarely      1222 Research & Development
## 587 587  38        No        Non-Travel       573 Research & Development
## 280 280  55        No     Travel_Rarely      1229 Research & Development
## 440 440  38        No     Travel_Rarely       827 Research & Development
## 389 389  36        No     Travel_Rarely       530                  Sales
## 499 499  36        No     Travel_Rarely      1299 Research & Development
## 251 251  33        No        Non-Travel      1313 Research & Development
## 231 231  45        No     Travel_Rarely      1329 Research & Development
## 564 564  31        No        Non-Travel       697 Research & Development
## 640 640  27       Yes     Travel_Rarely      1420                  Sales
## 463 463  50        No Travel_Frequently       809                  Sales
## 100 100  34        No     Travel_Rarely       401 Research & Development
## 731 731  43        No     Travel_Rarely       177 Research & Development
## 141 141  56        No     Travel_Rarely      1369 Research & Development
## 841 841  18       Yes     Travel_Rarely       230 Research & Development
## 745 745  25        No     Travel_Rarely      1382                  Sales
## 36   36  32        No Travel_Frequently      1311 Research & Development
## 792 792  34        No     Travel_Rarely       629 Research & Development
## 362 362  29       Yes Travel_Frequently       746                  Sales
## 86   86  59        No     Travel_Rarely       715 Research & Development
## 138 138  54        No     Travel_Rarely      1441 Research & Development
## 344 344  30        No Travel_Frequently       160 Research & Development
## 211 211  41        No     Travel_Rarely       582 Research & Development
## 461 461  42        No Travel_Frequently      1474 Research & Development
## 591 591  22        No        Non-Travel       457 Research & Development
## 829 829  38        No Travel_Frequently       594 Research & Development
## 672 672  33        No     Travel_Rarely       392                  Sales
## 653 653  40        No Travel_Frequently       593 Research & Development
## 832 832  19       Yes     Travel_Rarely       528                  Sales
## 371 371  31        No Travel_Frequently       853 Research & Development
## 380 380  30       Yes     Travel_Rarely       138 Research & Development
## 97   97  46        No     Travel_Rarely       228                  Sales
## 49   49  18       Yes Travel_Frequently      1306                  Sales
## 469 469  26       Yes        Non-Travel       265                  Sales
## 260 260  25        No     Travel_Rarely       977 Research & Development
## 650 650  40       Yes     Travel_Rarely      1329 Research & Development
## 174 174  33        No     Travel_Rarely       536                  Sales
## 775 775  42        No Travel_Frequently       288 Research & Development
## 554 554  48        No     Travel_Rarely      1469 Research & Development
## 723 723  34        No Travel_Frequently       560 Research & Development
## 183 183  43        No Travel_Frequently       957 Research & Development
## 347 347  34        No Travel_Frequently      1003 Research & Development
## 74   74  41        No     Travel_Rarely       167 Research & Development
## 641 641  30        No     Travel_Rarely      1358 Research & Development
## 631 631  55        No     Travel_Rarely       836 Research & Development
## 118 118  29        No     Travel_Rarely      1378 Research & Development
## 271 271  45        No        Non-Travel       589                  Sales
## 551 551  41        No     Travel_Rarely       314        Human Resources
## 763 763  41        No        Non-Travel       256                  Sales
## 357 357  26        No     Travel_Rarely       841 Research & Development
## 252 252  36        No        Non-Travel      1229                  Sales
## 619 619  39        No     Travel_Rarely       613 Research & Development
## 566 566  44        No     Travel_Rarely      1037 Research & Development
## 459 459  56        No     Travel_Rarely      1255 Research & Development
## 61   61  36       Yes     Travel_Rarely       530                  Sales
## 179 179  32        No Travel_Frequently       967                  Sales
## 272 272  34        No     Travel_Rarely      1130 Research & Development
## 76   76  30        No Travel_Frequently       721 Research & Development
## 87   87  47        No     Travel_Rarely       703                  Sales
## 224 224  28        No     Travel_Rarely      1423 Research & Development
## 739 739  35        No     Travel_Rarely      1219                  Sales
## 164 164  42        No     Travel_Rarely       916 Research & Development
## 13   13  35        No     Travel_Rarely       950 Research & Development
## 526 526  53        No Travel_Frequently       124                  Sales
## 836 836  37        No        Non-Travel       142                  Sales
## 693 693  42        No     Travel_Rarely      1332 Research & Development
## 545 545  34        No     Travel_Rarely       121 Research & Development
## 334 334  27        No     Travel_Rarely       608 Research & Development
## 95   95  50        No     Travel_Rarely      1452 Research & Development
## 657 657  51        No     Travel_Rarely      1469 Research & Development
## 269 269  33        No Travel_Frequently      1303 Research & Development
## 53   53  44        No     Travel_Rarely      1117 Research & Development
## 367 367  34        No Travel_Frequently       135 Research & Development
## 420 420  29        No     Travel_Rarely       986 Research & Development
## 54   54  45        No        Non-Travel       805 Research & Development
## 383 383  48        No     Travel_Rarely      1221                  Sales
## 571 571  41        No     Travel_Rarely       337                  Sales
## 274 274  36        No     Travel_Rarely       329                  Sales
## 773 773  39        No Travel_Frequently       505 Research & Development
## 168 168  33        No     Travel_Rarely       922 Research & Development
## 786 786  31        No     Travel_Rarely       182 Research & Development
## 546 546  34        No     Travel_Rarely       678 Research & Development
## 191 191  30        No     Travel_Rarely      1275 Research & Development
## 572 572  21       Yes     Travel_Rarely      1427 Research & Development
## 673 673  28        No Travel_Frequently       467                  Sales
## 67   67  35        No     Travel_Rarely      1017 Research & Development
## 580 580  29        No     Travel_Rarely      1329 Research & Development
## 869 869  45        No     Travel_Rarely      1457 Research & Development
## 277 277  22        No     Travel_Rarely       253 Research & Development
## 828 828  34        No     Travel_Rarely       131                  Sales
## 34   34  35        No     Travel_Rarely       982 Research & Development
## 504 504  29        No     Travel_Rarely      1389 Research & Development
## 586 586  40        No     Travel_Rarely       905 Research & Development
## 562 562  58        No Travel_Frequently      1216 Research & Development
## 618 618  44        No     Travel_Rarely      1488                  Sales
## 615 615  30        No     Travel_Rarely       231                  Sales
## 694 694  30       Yes Travel_Frequently       464 Research & Development
## 127 127  32       Yes Travel_Frequently      1125 Research & Development
## 31   31  32        No Travel_Frequently       689                  Sales
## 793 793  38        No     Travel_Rarely       397 Research & Development
## 830 830  50        No Travel_Frequently      1246        Human Resources
## 308 308  34        No        Non-Travel       697 Research & Development
## 863 863  34       Yes        Non-Travel      1362                  Sales
## 68   68  23        No     Travel_Rarely       571 Research & Development
## 707 707  54        No     Travel_Rarely       431 Research & Development
## 807 807  25        No     Travel_Rarely      1372                  Sales
## 351 351  42        No     Travel_Rarely      1396 Research & Development
## 582 582  42        No     Travel_Rarely       810 Research & Development
## 11   11  43        No     Travel_Rarely       823 Research & Development
## 149 149  24        No     Travel_Rarely       477 Research & Development
## 666 666  29        No Travel_Frequently       461 Research & Development
## 857 857  30       Yes     Travel_Rarely      1005 Research & Development
## 589 589  37        No     Travel_Rarely      1462 Research & Development
## 349 349  44        No        Non-Travel       111 Research & Development
## 742 742  31        No     Travel_Rarely       688                  Sales
## 648 648  26        No     Travel_Rarely       390 Research & Development
## 199 199  44        No     Travel_Rarely       477 Research & Development
## 624 624  35        No     Travel_Rarely      1146        Human Resources
## 565 565  30        No     Travel_Rarely       921 Research & Development
## 310 310  25        No     Travel_Rarely       810                  Sales
## 754 754  46       Yes     Travel_Rarely      1254                  Sales
## 604 604  29        No     Travel_Rarely      1401 Research & Development
## 795 795  49        No        Non-Travel      1002 Research & Development
## 519 519  30        No     Travel_Rarely      1138 Research & Development
## 295 295  40        No     Travel_Rarely       898        Human Resources
## 558 558  34        No     Travel_Rarely       254 Research & Development
## 364 364  40        No     Travel_Rarely      1416 Research & Development
## 408 408  36        No     Travel_Rarely       917 Research & Development
## 567 567  32        No     Travel_Rarely       128 Research & Development
## 235 235  43        No Travel_Frequently       394                  Sales
## 122 122  21        No     Travel_Rarely       501                  Sales
## 628 628  38        No     Travel_Rarely       343 Research & Development
## 157 157  40        No     Travel_Rarely       444                  Sales
## 819 819  30        No     Travel_Rarely      1427 Research & Development
## 821 821  32        No     Travel_Rarely       634 Research & Development
## 120 120  34        No     Travel_Rarely       404 Research & Development
## 346 346  39        No     Travel_Rarely       119                  Sales
## 539 539  24       Yes     Travel_Rarely      1448                  Sales
## 439 439  50       Yes     Travel_Rarely       869                  Sales
## 256 256  43        No        Non-Travel       343 Research & Development
## 498 498  37        No Travel_Frequently       889 Research & Development
## 679 679  36        No Travel_Frequently       688 Research & Development
## 165 165  35        No     Travel_Rarely      1232                  Sales
## 352 352  31        No     Travel_Rarely       218                  Sales
## 198 198  49        No     Travel_Rarely       174                  Sales
## 353 353  40        No Travel_Frequently       902 Research & Development
## 758 758  49        No     Travel_Rarely      1495 Research & Development
## 852 852  30        No     Travel_Rarely       125 Research & Development
## 330 330  42        No     Travel_Rarely      1147        Human Resources
## 152 152  32        No     Travel_Rarely       929                  Sales
## 404 404  36        No     Travel_Rarely       711 Research & Development
## 384 384  23        No     Travel_Rarely       541                  Sales
## 454 454  33        No     Travel_Rarely       217                  Sales
## 418 418  36        No Travel_Frequently       566 Research & Development
## 372 372  30        No        Non-Travel      1398                  Sales
## 106 106  26        No     Travel_Rarely      1384 Research & Development
## 285 285  38        No     Travel_Rarely       433        Human Resources
## 23   23  43        No Travel_Frequently      1001 Research & Development
## 399 399  56        No        Non-Travel       667 Research & Development
## 465 465  43       Yes Travel_Frequently       807 Research & Development
## 1     1  32        No     Travel_Rarely       117                  Sales
## 583 583  38        No     Travel_Rarely       833 Research & Development
## 241 241  42        No     Travel_Rarely       319 Research & Development
## 51   51  38        No     Travel_Rarely       362 Research & Development
## 255 255  40        No        Non-Travel       218 Research & Development
## 470 470  53        No     Travel_Rarely      1084 Research & Development
## 341 341  36        No     Travel_Rarely       852 Research & Development
## 45   45  23        No     Travel_Rarely       373 Research & Development
## 121 121  36        No        Non-Travel       427 Research & Development
## 507 507  33       Yes     Travel_Rarely       350                  Sales
## 710 710  50        No        Non-Travel       881 Research & Development
## 348 348  26        No Travel_Frequently      1479 Research & Development
## 381 381  47        No     Travel_Rarely      1482 Research & Development
## 201 201  40       Yes        Non-Travel      1479                  Sales
## 581 581  25        No     Travel_Rarely       882 Research & Development
## 517 517  25       Yes     Travel_Rarely       867                  Sales
## 419 419  37        No     Travel_Rarely       977 Research & Development
## 772 772  46        No     Travel_Rarely       526                  Sales
## 64   64  18        No        Non-Travel      1431 Research & Development
## 223 223  33        No        Non-Travel       530                  Sales
## 146 146  29        No        Non-Travel       746                  Sales
## 25   25  33        No     Travel_Rarely      1069 Research & Development
## 446 446  47        No     Travel_Rarely       465 Research & Development
## 448 448  42        No     Travel_Rarely      1128 Research & Development
## 150 150  28        No     Travel_Rarely       580 Research & Development
## 782 782  39        No     Travel_Rarely       408 Research & Development
## 853 853  29        No     Travel_Rarely       153 Research & Development
## 766 766  45        No     Travel_Rarely      1015 Research & Development
## 537 537  38        No     Travel_Rarely       130                  Sales
## 2     2  40        No     Travel_Rarely      1308 Research & Development
## 161 161  30        No     Travel_Rarely       852 Research & Development
## 75   75  52       Yes     Travel_Rarely      1030                  Sales
## 318 318  24        No     Travel_Rarely       771 Research & Development
## 414 414  32        No Travel_Frequently      1318                  Sales
## 681 681  25        No     Travel_Rarely       583                  Sales
## 186 186  28        No     Travel_Rarely      1158 Research & Development
## 135 135  43        No Travel_Frequently       559 Research & Development
## 732 732  39       Yes     Travel_Rarely      1162                  Sales
## 785 785  47        No        Non-Travel       543                  Sales
## 770 770  45        No        Non-Travel      1050                  Sales
## 801 801  33        No Travel_Frequently      1141                  Sales
## 779 779  26        No        Non-Travel       786 Research & Development
## 547 547  49        No     Travel_Rarely       527 Research & Development
## 278 278  43        No Travel_Frequently       185 Research & Development
## 555 555  40        No        Non-Travel      1151 Research & Development
## 263 263  33       Yes     Travel_Rarely       813 Research & Development
## 438 438  26        No     Travel_Rarely       157 Research & Development
## 206 206  44        No     Travel_Rarely       661 Research & Development
## 302 302  35        No Travel_Frequently       853                  Sales
## 192 192  31        No Travel_Frequently      1125                  Sales
## 590 590  35        No     Travel_Rarely      1142 Research & Development
## 834 834  19        No     Travel_Rarely       645 Research & Development
## 768 768  40        No        Non-Travel      1094                  Sales
## 733 733  27       Yes Travel_Frequently      1337        Human Resources
## 237 237  42        No     Travel_Rarely       300 Research & Development
## 321 321  32        No        Non-Travel      1184 Research & Development
## 125 125  29        No Travel_Frequently       442                  Sales
## 784 784  33        No Travel_Frequently      1146                  Sales
## 286 286  33        No     Travel_Rarely       589 Research & Development
## 682 682  43        No Travel_Frequently       313 Research & Development
## 143 143  46        No     Travel_Rarely       566 Research & Development
## 275 275  55        No     Travel_Rarely       692 Research & Development
## 436 436  27        No     Travel_Rarely      1130                  Sales
## 156 156  30        No        Non-Travel       641                  Sales
## 532 532  36        No     Travel_Rarely       884                  Sales
## 842 842  29        No     Travel_Rarely       332        Human Resources
## 747 747  29       Yes     Travel_Rarely       350        Human Resources
## 866 866  48        No     Travel_Rarely       855 Research & Development
## 113 113  52        No     Travel_Rarely       994 Research & Development
## 535 535  29       Yes     Travel_Rarely       318 Research & Development
## 596 596  33        No     Travel_Rarely       586                  Sales
## 162 162  28       Yes        Non-Travel      1366 Research & Development
## 825 825  36        No     Travel_Rarely       559 Research & Development
## 728 728  34        No Travel_Frequently       878 Research & Development
## 332 332  32       Yes     Travel_Rarely      1045                  Sales
## 702 702  34        No     Travel_Rarely      1400                  Sales
## 870 870  35        No Travel_Frequently       138 Research & Development
## 636 636  35        No Travel_Frequently       636 Research & Development
## 777 777  30        No     Travel_Rarely       330        Human Resources
## 128 128  45        No     Travel_Rarely       556 Research & Development
## 610 610  33        No        Non-Travel      1038                  Sales
## 818 818  33        No     Travel_Rarely       213 Research & Development
## 451 451  33        No     Travel_Rarely       501 Research & Development
## 712 712  57        No     Travel_Rarely       210                  Sales
## 490 490  34        No     Travel_Rarely       970 Research & Development
## 222 222  45       Yes Travel_Frequently       306                  Sales
## 647 647  18       Yes        Non-Travel       247 Research & Development
## 85   85  36        No     Travel_Rarely       429 Research & Development
## 806 806  36        No     Travel_Rarely      1383 Research & Development
## 516 516  51        No     Travel_Rarely      1302 Research & Development
## 637 637  42        No     Travel_Rarely       469 Research & Development
## 159 159  43        No Travel_Frequently      1082 Research & Development
## 289 289  36        No Travel_Frequently      1467                  Sales
## 635 635  43        No     Travel_Rarely      1001 Research & Development
## 464 464  31        No Travel_Frequently       163 Research & Development
## 654 654  48        No     Travel_Rarely       530                  Sales
## 299 299  31       Yes        Non-Travel       335 Research & Development
## 788 788  52       Yes     Travel_Rarely       723 Research & Development
## 761 761  29       Yes     Travel_Rarely       906 Research & Development
## 664 664  35        No     Travel_Rarely       802 Research & Development
## 331 331  49        No     Travel_Rarely       809 Research & Development
## 204 204  28       Yes     Travel_Rarely       654 Research & Development
## 57   57  42       Yes Travel_Frequently       933 Research & Development
## 29   29  53       Yes     Travel_Rarely      1168                  Sales
## 734 734  32       Yes        Non-Travel      1474                  Sales
## 55   55  31        No     Travel_Rarely       746 Research & Development
## 862 862  43        No     Travel_Rarely       531                  Sales
## 279 279  25       Yes     Travel_Rarely       240                  Sales
## 472 472  29       Yes Travel_Frequently       459 Research & Development
## 190 190  28        No        Non-Travel       120                  Sales
## 132 132  49        No     Travel_Rarely      1313                  Sales
## 409 409  53        No     Travel_Rarely      1219                  Sales
## 557 557  54        No     Travel_Rarely       548 Research & Development
## 340 340  27        No     Travel_Rarely      1240 Research & Development
## 437 437  28       Yes     Travel_Rarely       890 Research & Development
## 844 844  34        No     Travel_Rarely       943 Research & Development
## 238 238  32        No     Travel_Rarely       646 Research & Development
## 329 329  38        No Travel_Frequently      1394 Research & Development
## 229 229  24        No     Travel_Rarely      1353                  Sales
## 423 423  31       Yes     Travel_Rarely       249                  Sales
## 805 805  44        No        Non-Travel       489 Research & Development
## 656 656  26        No Travel_Frequently       496 Research & Development
## 435 435  40        No     Travel_Rarely       658                  Sales
## 492 492  50        No     Travel_Rarely      1322 Research & Development
## 187 187  25        No Travel_Frequently       772 Research & Development
## 575 575  26        No     Travel_Rarely       703                  Sales
## 671 671  37        No     Travel_Rarely       397 Research & Development
## 560 560  26        No     Travel_Rarely       933                  Sales
## 401 401  30        No     Travel_Rarely       317 Research & Development
## 176 176  21        No     Travel_Rarely       984 Research & Development
## 715 715  36        No        Non-Travel      1434                  Sales
## 621 621  20       Yes Travel_Frequently       871 Research & Development
## 823 823  34        No     Travel_Rarely       704                  Sales
## 815 815  38        No     Travel_Rarely       395                  Sales
## 133 133  42        No Travel_Frequently      1368 Research & Development
## 425 425  28        No     Travel_Rarely       736                  Sales
## 38   38  36       Yes     Travel_Rarely      1456                  Sales
## 692 692  47       Yes        Non-Travel       666 Research & Development
## 292 292  36        No        Non-Travel      1105 Research & Development
## 690 690  38        No        Non-Travel      1336        Human Resources
## 833 833  28        No     Travel_Rarely      1179 Research & Development
## 503 503  48       Yes Travel_Frequently       708                  Sales
## 21   21  36        No     Travel_Rarely       913 Research & Development
## 112 112  52        No     Travel_Rarely      1053 Research & Development
## 124 124  38        No     Travel_Rarely       243                  Sales
## 422 422  37        No        Non-Travel      1063 Research & Development
## 91   91  38        No Travel_Frequently      1490 Research & Development
## 259 259  34        No     Travel_Rarely      1480                  Sales
## 453 453  35       Yes     Travel_Rarely       303                  Sales
## 35   35  32        No     Travel_Rarely      1373 Research & Development
## 17   17  32        No     Travel_Rarely       498 Research & Development
## 677 677  36        No     Travel_Rarely       676 Research & Development
## 415 415  34       Yes Travel_Frequently       296                  Sales
## 813 813  24        No     Travel_Rarely      1371                  Sales
## 32   32  33        No     Travel_Rarely       267 Research & Development
## 320 320  19        No     Travel_Rarely       265 Research & Development
## 496 496  51        No     Travel_Rarely      1318                  Sales
## 225 225  38        No     Travel_Rarely      1206 Research & Development
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## 597    Manufacturing Director               2       Married         10903
## 771           Sales Executive               4        Single          4682
## 160         Research Director               1       Married         13191
## 77            Sales Executive               3       Married          7083
## 529        Research Scientist               3        Single          2859
## 126           Sales Executive               4       Married          5204
## 262        Research Scientist               1        Single          2362
## 442     Laboratory Technician               3       Married          2974
## 642 Healthcare Representative               1      Divorced          4448
## 181    Manufacturing Director               2      Divorced         10274
## 163           Sales Executive               3      Divorced          7104
## 474        Research Scientist               4        Single          3452
## 228        Research Scientist               2      Divorced          2328
## 774        Research Scientist               3       Married          3388
## 646           Sales Executive               4       Married         10855
## 265     Laboratory Technician               3       Married          2774
## 427        Research Scientist               3      Divorced          1274
## 781      Sales Representative               2        Single          3140
## 249        Research Scientist               4      Divorced          5467
## 810        Research Scientist               2       Married          3058
## 40       Sales Representative               4       Married          2791
## 541     Laboratory Technician               3      Divorced          3491
## 497        Research Scientist               4       Married          2654
## 697                   Manager               4       Married         15202
## 865    Manufacturing Director               4       Married          9380
## 450           Sales Executive               1       Married          4385
## 600        Research Scientist               4       Married          2293
## 778      Sales Representative               1      Divorced          2827
## 363                   Manager               4       Married         19845
## 478           Sales Executive               3      Divorced          4306
## 403     Laboratory Technician               3        Single          2105
## 375      Sales Representative               1        Single          2728
## 335                   Manager               4       Married         18844
## 598     Laboratory Technician               3       Married          3448
## 142        Research Scientist               3      Divorced          2372
## 444           Human Resources               4      Divorced          3195
## 741           Sales Executive               3       Married          8639
## 659    Manufacturing Director               2        Single          6032
## 790        Research Scientist               2        Single          2096
## 457           Sales Executive               4       Married          5476
## 188                   Manager               2      Divorced         15972
## 432        Research Scientist               3      Divorced          3544
## 488        Research Scientist               3      Divorced          2911
## 538           Human Resources               3      Divorced          2696
## 752      Sales Representative               2        Single          2302
## 215        Research Scientist               4        Single          2045
## 540           Sales Executive               1        Single          5155
## 613     Laboratory Technician               1       Married          2707
## 730     Laboratory Technician               4       Married          2523
## 296     Laboratory Technician               3       Married          2660
## 328        Research Scientist               1      Divorced          5410
## 147        Research Scientist               2       Married          2756
## 701           Human Resources               2       Married          2804
## 708           Human Resources               2        Single          2109
## 84         Research Scientist               1      Divorced          5974
## 83     Manufacturing Director               3       Married          5321
## 250                   Manager               1       Married         16595
## 767        Research Scientist               3       Married          3376
## 281           Sales Executive               4       Married          7847
## 675        Research Scientist               3       Married          3517
## 843    Manufacturing Director               4       Married         13826
## 431           Sales Executive               3        Single          4478
## 30         Research Scientist               4       Married          4258
## 10  Healthcare Representative               3       Married          5063
## 817    Manufacturing Director               4        Single          6877
## 441        Research Scientist               3        Single          4998
## 820           Sales Executive               3        Single          9854
## 345           Sales Executive               1      Divorced          4115
## 592           Sales Executive               2        Single          4599
## 585 Healthcare Representative               4       Married          6465
## 660    Manufacturing Director               2        Single          6499
## 12            Human Resources               4      Divorced          2706
## 293        Research Scientist               2        Single          2279
## 303        Research Scientist               2      Divorced          3537
## 738           Sales Executive               4        Single          5171
## 678     Laboratory Technician               3       Married          6323
## 338 Healthcare Representative               4        Single          7756
## 350 Healthcare Representative               4       Married         11103
## 720    Manufacturing Director               2      Divorced          7655
## 658                   Manager               4      Divorced         16032
## 107    Manufacturing Director               3       Married          4319
## 543        Research Scientist               3      Divorced          2566
## 518     Laboratory Technician               2      Divorced          2766
## 854 Healthcare Representative               1        Single          5661
## 43      Laboratory Technician               1      Divorced          2587
## 189         Research Director               2      Divorced         19144
## 171           Sales Executive               4      Divorced          5304
## 39                    Manager               2        Single         19717
## 216        Research Scientist               3      Divorced          2345
## 291     Laboratory Technician               4      Divorced          2270
## 58      Laboratory Technician               1        Single          4723
## 395        Research Scientist               4        Single          2515
## 856      Sales Representative               3       Married          2404
## 456                   Manager               2        Single         19833
## 22            Sales Executive               2       Married          8120
## 170        Research Scientist               4      Divorced          2514
## 588      Sales Representative               1        Single          3407
## 63       Sales Representative               3       Married          3067
## 676                   Manager               2       Married         18789
## 719           Sales Executive               4        Single          4581
## 417     Laboratory Technician               4        Single          2564
## 789         Research Director               1       Married         19038
## 70         Research Scientist               4        Single          2115
## 59          Research Director               4      Divorced         13603
## 800 Healthcare Representative               1      Divorced          6842
## 484        Research Scientist               1      Divorced          4257
## 203    Manufacturing Director               3       Married          6162
## 227     Laboratory Technician               4      Divorced          1951
## 243        Research Scientist               2       Married          2703
## 413        Research Scientist               2       Married          3022
## 577      Sales Representative               1        Single          2858
## 542        Research Scientist               1       Married          3143
## 476           Sales Executive               4        Single          5772
## 744     Laboratory Technician               2        Single          3295
## 804           Sales Executive               1        Single          9582
## 405        Research Scientist               1        Single          2559
## 397         Research Director               3       Married         17861
## 607           Sales Executive               3        Single          5473
## 501    Manufacturing Director               1       Married         10008
## 429     Laboratory Technician               3        Single          3730
## 205      Sales Representative               2       Married          3931
## 475     Laboratory Technician               3      Divorced          2207
## 104        Research Scientist               1       Married          2819
## 210           Sales Executive               3      Divorced          8189
## 471        Research Scientist               2       Married          2226
## 66         Research Scientist               2      Divorced          3298
## 88      Laboratory Technician               2      Divorced          3743
## 826         Research Director               4      Divorced         19627
## 601      Sales Representative               2       Married          2033
## 309 Healthcare Representative               2       Married          6385
## 737           Sales Executive               4       Married         12031
## 294         Research Director               2       Married         11957
## 421    Manufacturing Director               2       Married          4325
## 769    Manufacturing Director               4      Divorced          7379
## 430    Manufacturing Director               1       Married          5957
## 512 Healthcare Representative               3       Married         10920
## 361                   Manager               3       Married         19999
## 814                   Manager               3       Married         19658
## 480         Research Director               4       Married         13744
## 15            Human Resources               1        Single          3423
## 486           Sales Executive               4        Single          5993
## 254           Human Resources               1       Married          2956
## 491         Research Director               1        Single         18665
## 713     Laboratory Technician               2        Single          2559
## 178        Research Scientist               1       Married          2042
## 428        Research Scientist               3        Single          3230
## 691           Human Resources               3       Married          6077
## 194           Sales Executive               4       Married          4051
## 599    Manufacturing Director               2       Married          6142
## 802           Sales Executive               4        Single          6582
## 378           Sales Executive               4      Divorced          5087
## 639        Research Scientist               4       Married          2725
## 155     Laboratory Technician               2      Divorced          2008
## 166      Sales Representative               3        Single          2044
## 207           Sales Executive               3        Single          5346
## 468     Laboratory Technician               4       Married          3038
## 105         Research Director               2        Single         16598
## 482        Research Scientist               4       Married          2356
## 587        Research Scientist               4      Divorced          5329
## 280 Healthcare Representative               3       Married          4035
## 440 Healthcare Representative               4        Single          7625
## 389      Sales Representative               4        Single          4502
## 499 Healthcare Representative               3       Married          5237
## 251     Laboratory Technician               3      Divorced          2008
## 231    Manufacturing Director               4      Divorced          5770
## 564         Research Director               3       Married         11031
## 640      Sales Representative               1      Divorced          3041
## 463           Sales Executive               4        Single          9208
## 100     Laboratory Technician               2       Married          3294
## 731    Manufacturing Director               2      Divorced          4765
## 141    Manufacturing Director               2       Married         13402
## 841     Laboratory Technician               3        Single          1420
## 745           Sales Executive               3      Divorced          4907
## 36      Laboratory Technician               2       Married          2794
## 792        Research Scientist               2        Single          2311
## 362      Sales Representative               1        Single          1091
## 86     Manufacturing Director               4        Single         13726
## 138    Manufacturing Director               3       Married         10739
## 344        Research Scientist               3      Divorced          2083
## 211    Manufacturing Director               2       Married         13570
## 461     Laboratory Technician               3       Married          2093
## 591        Research Scientist               3       Married          2814
## 829     Laboratory Technician               2       Married          2468
## 672           Sales Executive               4      Divorced          5505
## 653         Research Director               3        Single         13499
## 832      Sales Representative               3        Single          1675
## 371    Manufacturing Director               1       Married          4148
## 380        Research Scientist               3       Married          2132
## 97                    Manager               2       Married         16606
## 49       Sales Representative               2        Single          1878
## 469           Sales Executive               1        Single          4969
## 260     Laboratory Technician               3      Divorced          3977
## 650     Laboratory Technician               1        Single          2166
## 174           Sales Executive               3      Divorced          8380
## 775 Healthcare Representative               4       Married         10124
## 554        Research Scientist               3       Married          2259
## 723        Research Scientist               1      Divorced          2996
## 183        Research Scientist               3        Single          4739
## 347    Manufacturing Director               3        Single          4033
## 74      Laboratory Technician               4       Married          4766
## 641     Laboratory Technician               3      Divorced          2693
## 631        Research Scientist               4       Married          2662
## 118     Laboratory Technician               2       Married          4025
## 271           Sales Executive               3       Married          5154
## 551                   Manager               3       Married         19189
## 763           Sales Executive               2        Single          6151
## 357        Research Scientist               2       Married          2368
## 252           Sales Executive               4      Divorced          5079
## 619 Healthcare Representative               1       Married          9991
## 566        Research Scientist               4        Single          2436
## 459        Research Scientist               1       Married          2066
## 61            Sales Executive               4       Married         10325
## 179           Sales Executive               4        Single          8998
## 272        Research Scientist               2      Divorced          5433
## 76      Laboratory Technician               4        Single          4011
## 87            Sales Executive               1        Single          4960
## 224        Research Scientist               3      Divorced          1563
## 739           Sales Executive               3       Married          4601
## 164        Research Scientist               1        Single          6545
## 13     Manufacturing Director               3        Single         10221
## 526           Sales Executive               2       Married          7525
## 836           Sales Executive               2      Divorced          8834
## 693 Healthcare Representative               4        Single          6781
## 545        Research Scientist               1        Single          4381
## 334    Manufacturing Director               1       Married          7412
## 95                    Manager               2        Single         19926
## 657         Research Director               2       Married         12490
## 269 Healthcare Representative               3      Divorced          5968
## 53         Research Scientist               4       Married          2011
## 367     Laboratory Technician               2      Divorced          4444
## 420         Research Director               3       Married         11935
## 54      Laboratory Technician               2       Married          4447
## 383           Sales Executive               1      Divorced          5486
## 571           Sales Executive               2       Married          4393
## 274           Sales Executive               1       Married          5647
## 773 Healthcare Representative               3        Single         10938
## 168         Research Director               3      Divorced         16184
## 786         Research Director               2        Single         16422
## 546        Research Scientist               4       Married          2929
## 191        Research Scientist               4       Married          5775
## 572        Research Scientist               4        Single          2693
## 673           Sales Executive               1        Single          4898
## 67         Research Scientist               4        Single          6646
## 580 Healthcare Representative               4      Divorced          6623
## 869        Research Scientist               3       Married          4477
## 277        Research Scientist               2       Married          2244
## 828           Sales Executive               1        Single          4538
## 34      Laboratory Technician               3       Married          2258
## 504    Manufacturing Director               1      Divorced          9980
## 586     Laboratory Technician               4       Married          2741
## 562         Research Director               3       Married         15787
## 618           Sales Executive               1      Divorced          5454
## 615           Sales Executive               3      Divorced          7264
## 694        Research Scientist               4        Single          2285
## 127        Research Scientist               1        Single          3919
## 31            Sales Executive               4      Divorced          4668
## 793    Manufacturing Director               3       Married          7756
## 830                   Manager               2       Married         18200
## 308        Research Scientist               4       Married          2979
## 863           Sales Executive               4        Single          5304
## 68      Laboratory Technician               4        Single          2647
## 707        Research Scientist               4       Married          6854
## 807           Sales Executive               3       Married          6232
## 351         Research Director               1       Married         13348
## 582         Research Director               4        Single         15992
## 11                    Manager               3       Married         19392
## 149     Laboratory Technician               2        Single          3597
## 666 Healthcare Representative               3        Single          6294
## 857        Research Scientist               1        Single          2657
## 589     Laboratory Technician               3        Single          3629
## 349        Research Scientist               3        Single          2290
## 742                   Manager               4      Divorced         11557
## 648     Laboratory Technician               3       Married          2305
## 199 Healthcare Representative               4       Married         10248
## 624           Human Resources               4        Single          8837
## 565     Laboratory Technician               3       Married          3833
## 310           Sales Executive               2       Married          4851
## 754           Sales Executive               2       Married          7314
## 604     Laboratory Technician               4       Married          3131
## 795    Manufacturing Director               4      Divorced          6804
## 519     Laboratory Technician               4       Married          4627
## 295                   Manager               4        Single         16437
## 558        Research Scientist               4       Married          3622
## 364         Research Director               3      Divorced         19436
## 408     Laboratory Technician               3      Divorced          2741
## 567     Laboratory Technician               1        Single          2176
## 235                   Manager               4       Married         16959
## 122      Sales Representative               1        Single          2380
## 628         Research Director               4      Divorced         11510
## 157           Sales Executive               2       Married          5677
## 819     Laboratory Technician               4        Single          2720
## 821        Research Scientist               4       Married          3312
## 120 Healthcare Representative               4        Single          6687
## 346           Sales Executive               1        Single         13341
## 539      Sales Representative               2        Single          3202
## 439      Sales Representative               3       Married          2683
## 256        Research Scientist               3        Single          2438
## 498        Research Scientist               4       Married          2326
## 679    Manufacturing Director               2      Divorced          5131
## 165           Sales Executive               2       Married          8020
## 352           Sales Executive               4       Married          6929
## 198           Sales Executive               2       Married         13120
## 353        Research Scientist               4       Married          4422
## 758 Healthcare Representative               3       Married          6651
## 852     Laboratory Technician               3        Single          2206
## 330                   Manager               1       Married         16799
## 152           Sales Executive               4        Single          5396
## 404 Healthcare Representative               1       Married          8008
## 384      Sales Representative               1      Divorced          2322
## 454           Sales Executive               3        Single          5487
## 418     Laboratory Technician               4       Married          3688
## 372           Sales Executive               1       Married          8412
## 106     Laboratory Technician               4       Married          4420
## 285           Human Resources               3       Married          2844
## 23      Laboratory Technician               3      Divorced          5679
## 399 Healthcare Representative               3      Divorced          6306
## 465        Research Scientist               3       Married          2437
## 1             Sales Executive               4      Divorced          4403
## 583 Healthcare Representative               4       Married          5811
## 241    Manufacturing Director               1       Married          7406
## 51         Research Scientist               1        Single          2619
## 255         Research Director               2      Divorced         13757
## 470    Manufacturing Director               1      Divorced          4450
## 341        Research Scientist               1       Married          3419
## 45         Research Scientist               3       Married          1223
## 121         Research Director               1       Married         11713
## 507      Sales Representative               3        Single          2851
## 710                   Manager               1      Divorced         17924
## 348    Manufacturing Director               2      Divorced          6397
## 381         Research Director               3       Married         18300
## 201           Sales Executive               2        Single         13194
## 581     Laboratory Technician               4       Married          3669
## 517      Sales Representative               2       Married          2413
## 419    Manufacturing Director               4       Married          6474
## 772           Sales Executive               1      Divorced         10453
## 64         Research Scientist               3        Single          1514
## 223           Sales Executive               4      Divorced          5368
## 146           Sales Executive               3       Married          4649
## 25  Healthcare Representative               4        Single          6949
## 446        Research Scientist               4       Married          3420
## 448 Healthcare Representative               1       Married          5538
## 150    Manufacturing Director               1      Divorced          4877
## 782 Healthcare Representative               3        Single          4553
## 853     Laboratory Technician               3        Single          4193
## 766     Laboratory Technician               1        Single          5769
## 537           Sales Executive               2        Single          7351
## 2           Research Director               3        Single         19626
## 161     Laboratory Technician               4       Married          5126
## 75            Sales Executive               2        Single          8446
## 318 Healthcare Representative               3        Single          4617
## 414           Sales Executive               4        Single          4648
## 681           Sales Executive               1       Married          4256
## 186        Research Scientist               4       Married          2070
## 135     Laboratory Technician               3      Divorced          5257
## 732           Sales Executive               3       Married          5238
## 785           Sales Executive               2       Married          4978
## 770           Sales Executive               3       Married          5593
## 801           Sales Executive               1       Married          5376
## 779     Laboratory Technician               4        Single          2570
## 547     Laboratory Technician               2       Married          7403
## 278     Laboratory Technician               4        Single          2455
## 555 Healthcare Representative               4       Married          4876
## 263     Laboratory Technician               4       Married          2436
## 438     Laboratory Technician               1        Single          2867
## 206        Research Scientist               1       Married          2559
## 302           Sales Executive               1       Married          9069
## 192           Sales Executive               1       Married          9637
## 590     Laboratory Technician               1       Married          4014
## 834        Research Scientist               1        Single          2552
## 768           Sales Executive               1      Divorced         10932
## 733           Human Resources               2       Married          2863
## 237                   Manager               3       Married         18880
## 321     Laboratory Technician               2       Married          2332
## 125           Sales Executive               4        Single          4554
## 784           Sales Executive               3       Married          4539
## 286     Laboratory Technician               3       Married          5207
## 682     Laboratory Technician               4       Married          2258
## 143    Manufacturing Director               3      Divorced         10845
## 275         Research Director               2        Single         18722
## 436           Sales Executive               2       Married          6214
## 156           Sales Executive               3       Married          4736
## 532           Sales Executive               3        Single          6815
## 842           Human Resources               1        Single          7988
## 747           Human Resources               1      Divorced          2335
## 866    Manufacturing Director               4        Single          7898
## 113 Healthcare Representative               2        Single         10445
## 535     Laboratory Technician               1       Married          2119
## 596           Sales Executive               1      Divorced          4037
## 162 Healthcare Representative               1        Single          8722
## 825    Manufacturing Director               3       Married          4663
## 728        Research Scientist               3      Divorced          3815
## 332           Sales Executive               4       Married         10400
## 702           Sales Executive               3       Married          5714
## 870     Laboratory Technician               2        Single          4425
## 636     Laboratory Technician               4       Married          2376
## 777           Human Resources               3      Divorced          2064
## 128    Manufacturing Director               4       Married          5906
## 610      Sales Representative               4        Single          2342
## 818         Research Director               3       Married         11691
## 451 Healthcare Representative               4       Married          4878
## 712                   Manager               4      Divorced         14118
## 490 Healthcare Representative               3        Single          6142
## 222           Sales Executive               1       Married          4286
## 647     Laboratory Technician               3        Single          1904
## 85     Manufacturing Director               2        Single          5410
## 806 Healthcare Representative               1       Married          8321
## 516    Manufacturing Director               2      Divorced          5482
## 637                   Manager               1       Married         17665
## 159    Manufacturing Director               1       Married         10820
## 289           Sales Executive               4       Married          9738
## 635 Healthcare Representative               1       Married          9985
## 464    Manufacturing Director               4        Single          5238
## 654                   Manager               3       Married         12504
## 299        Research Scientist               1        Single          2321
## 788        Research Scientist               2       Married          4941
## 761        Research Scientist               1        Single          2404
## 664     Laboratory Technician               4      Divorced          3917
## 331                   Manager               3        Single         15379
## 204        Research Scientist               2        Single          2216
## 57         Research Scientist               3      Divorced          2759
## 29            Sales Executive               1        Single         10448
## 734           Sales Executive               3       Married          4707
## 55     Manufacturing Director               4        Single          4424
## 862           Sales Executive               4        Single         10231
## 279           Sales Executive               3        Single          5744
## 472        Research Scientist               4        Single          2439
## 190           Sales Executive               3       Married          4221
## 132           Sales Executive               4        Single          4507
## 409                   Manager               4       Married         15427
## 557     Laboratory Technician               3        Single          3780
## 340     Laboratory Technician               1      Divorced          2341
## 437        Research Scientist               3        Single          4382
## 844 Healthcare Representative               4      Divorced          8500
## 238        Research Scientist               4       Married          6322
## 329        Research Scientist               2      Divorced          2133
## 229           Sales Executive               3       Married          4999
## 423           Sales Executive               3       Married          6172
## 805     Laboratory Technician               2       Married          2042
## 656 Healthcare Representative               1       Married          4741
## 435           Sales Executive               2      Divorced          9705
## 492         Research Director               1       Married         16880
## 187    Manufacturing Director               3      Divorced          5206
## 575           Sales Executive               2       Married          6272
## 671         Research Director               3        Single         13664
## 560           Sales Executive               3       Married          5296
## 401    Manufacturing Director               4        Single          6091
## 176        Research Scientist               2        Single          2070
## 715           Sales Executive               1        Single          7587
## 621     Laboratory Technician               4        Single          2926
## 823           Sales Executive               3       Married          6712
## 815      Sales Representative               2       Married          2899
## 133 Healthcare Representative               4       Married          4523
## 425           Sales Executive               1       Married          4724
## 38            Sales Executive               1      Divorced          6134
## 692                   Manager               2       Married         11849
## 292     Laboratory Technician               2       Married          5674
## 690           Human Resources               2      Divorced          2592
## 833     Laboratory Technician               1       Married          3196
## 503      Sales Representative               3       Married          2655
## 21     Manufacturing Director               2      Divorced          8847
## 112                   Manager               4       Married         17099
## 124           Sales Executive               4        Single          4028
## 422        Research Scientist               3       Married          4449
## 91      Laboratory Technician               4       Married          1702
## 259           Sales Executive               4       Married          9713
## 453           Sales Executive               4        Single          5813
## 35     Manufacturing Director               4        Single          9679
## 17     Manufacturing Director               1       Married          6725
## 677    Manufacturing Director               2       Married          5228
## 415      Sales Representative               3      Divorced          2351
## 813           Sales Executive               3      Divorced          4260
## 32      Laboratory Technician               2       Married          2028
## 320        Research Scientist               4        Single          2994
## 496                   Manager               3       Married         16307
## 225        Research Scientist               4      Divorced          4771
## 226     Laboratory Technician               2       Married          3748
## 385        Research Scientist               3       Married          2461
## 700         Research Director               2       Married         19081
## 411           Human Resources               1       Married          2342
## 822           Sales Executive               4      Divorced          6931
## 393        Research Scientist               1      Divorced          3065
## 799        Research Scientist               2        Single          1859
## 324        Research Scientist               1      Divorced          4615
## 267         Research Director               1      Divorced         17007
## 698     Laboratory Technician               2        Single          5914
## 264      Sales Representative               4       Married          2157
## 110        Research Scientist               1        Single          2439
## 494 Healthcare Representative               2        Single          8606
## 42       Sales Representative               3        Single          6632
## 245    Manufacturing Director               4       Married          5056
## 489     Laboratory Technician               3        Single          5381
## 300        Research Scientist               4       Married          3464
## 652           Sales Executive               4      Divorced          5220
## 688        Research Scientist               2       Married          2622
## 94  Healthcare Representative               3        Single          6142
## 377     Laboratory Technician               1        Single          2743
## 467      Sales Representative               4        Single          2644
## 394           Sales Executive               1       Married         10266
## 445         Research Director               4      Divorced         19328
## 524         Research Director               3      Divorced         19502
## 680      Sales Representative               3       Married          2329
## 253        Research Scientist               3        Single          2274
## 177                   Manager               1       Married         19859
## 500           Sales Executive               3       Married          5736
## 506        Research Scientist               2       Married          5878
## 858    Manufacturing Director               3       Married          8943
## 549         Research Director               2       Married         12061
## 674        Research Scientist               2      Divorced          2022
## 443     Laboratory Technician               3        Single          3485
## 14       Sales Representative               2       Married          2476
## 333        Research Scientist               2      Divorced          2342
## 663           Sales Executive               4      Divorced         10368
## 530        Research Scientist               2       Married          4963
## 3      Manufacturing Director               4        Single          9362
## 523        Research Scientist               1      Divorced          9724
## 369        Research Scientist               3       Married          2073
## 129        Research Scientist               3        Single          4081
## 633           Sales Executive               4        Single          6861
## 48            Sales Executive               3      Divorced          8740
## 325    Manufacturing Director               4       Married         12742
## 845           Sales Executive               4        Single          6029
## 7          Research Scientist               3       Married          2127
## 847     Laboratory Technician               2        Single          1483
## 716           Human Resources               3       Married          1555
## 28            Sales Executive               1        Single          8224
## 230 Healthcare Representative               3       Married         13966
## 416    Manufacturing Director               4      Divorced          5762
## 373     Laboratory Technician               1      Divorced          5210
## 809        Research Scientist               4       Married          2862
## 729     Laboratory Technician               4        Single          2340
## 812     Laboratory Technician               4       Married          3229
## 528 Healthcare Representative               1       Married          6833
## 37            Sales Executive               1       Married         10306
## 705           Human Resources               3       Married          2267
## 354 Healthcare Representative               4      Divorced          4069
## 563     Laboratory Technician               2       Married          2811
## 559    Manufacturing Director               2       Married          4434
## 525        Research Scientist               4       Married          2177
## 868           Sales Executive               3       Married          4591
## 27            Sales Executive               2       Married          9924
## 755         Research Director               3       Married         13549
## 594     Laboratory Technician               1       Married          3211
## 520     Laboratory Technician               4        Single          2587
## 287        Research Scientist               2        Single          2472
## 620     Laboratory Technician               3       Married          1281
## 753 Healthcare Representative               3       Married         11245
## 65      Laboratory Technician               2       Married          2210
## 154 Healthcare Representative               2        Single          6870
## 662        Research Scientist               3      Divorced          2768
## 247    Manufacturing Director               4        Single          7143
## 850     Laboratory Technician               4       Married          2544
## 33                    Manager               2       Married         16872
## 550           Human Resources               2        Single          2177
## 797 Healthcare Representative               4       Married         13496
## 509      Sales Representative               4      Divorced          2793
## 24            Sales Executive               1        Single          5332
## 185     Laboratory Technician               3       Married          3755
## 513        Research Scientist               3       Married          3433
## 553           Human Resources               4        Single          3886
## 455                   Manager               1       Married         15402
## 477           Sales Executive               3      Divorced          6334
## 360     Laboratory Technician               4       Married          3210
## 846     Laboratory Technician               1      Divorced          4558
## 217 Healthcare Representative               3       Married          9824
## 765           Human Resources               4       Married          3737
## 714           Sales Executive               4       Married          9699
## 593      Sales Representative               3       Married          2909
## 699      Sales Representative               4        Single          1569
## 762                   Manager               4       Married         16752
## 824     Laboratory Technician               3       Married          2610
## 407           Sales Executive               4       Married          5468
## 391           Sales Executive               1       Married          6500
## 153           Sales Executive               3       Married          5484
## 433     Laboratory Technician               1        Single          4284
## 82     Manufacturing Director               3       Married          6883
## 831     Laboratory Technician               1       Married          3633
## 232      Sales Representative               4       Married          2014
## 796        Research Scientist               1        Single          3348
## 685        Research Scientist               4       Married          2713
## 317      Sales Representative               3       Married          2231
## 242                   Manager               2        Single         18061
## 290      Sales Representative               4       Married          2572
## 119        Research Scientist               3      Divorced          2451
## 808        Research Scientist               4       Married          2323
## 6      Manufacturing Director               1      Divorced          8793
## 311        Research Scientist               4       Married          5484
## 392           Sales Executive               4       Married          4157
## 481 Healthcare Representative               1       Married          5373
## 114 Healthcare Representative               1      Divorced          5093
## 864           Sales Executive               3      Divorced         13770
## 683 Healthcare Representative               3       Married          5347
## 368           Sales Executive               1       Married          5473
## 622    Manufacturing Director               3      Divorced          5067
## 314    Manufacturing Director               3       Married          6132
## 306     Laboratory Technician               4       Married          3162
## 412           Sales Executive               3        Single          9241
## 219        Research Scientist               3        Single          2632
##     MonthlyRate NumCompaniesWorked OverTime PercentSalaryHike PerformanceRating
## 284        7143                  4       No                12                 3
## 848       10942                  0       No                17                 3
## 101        7679                  0       No                14                 3
## 623       13551                  2       No                16                 3
## 645       20293                  6       No                17                 3
## 400       19719                  5      Yes                18                 3
## 98        15850                  5       No                14                 3
## 103       12740                  9       No                15                 3
## 726        7505                  0       No                12                 3
## 602       25174                  4       No                14                 3
## 326       17808                  1       No                19                 3
## 79        16840                  6       No                12                 3
## 270        9096                  0       No                15                 3
## 382        8916                  1       No                23                 4
## 184        9150                  4       No                18                 3
## 574       22128                  1       No                21                 4
## 4         24032                  1       No                19                 3
## 661       21146                  1       No                15                 3
## 552       23965                  1       No                13                 3
## 212        7770                  6       No                13                 3
## 195        4050                  0       No                12                 3
## 511        5982                  1       No                11                 3
## 479       17363                  9       No                13                 3
## 605       14630                  1       No                13                 3
## 634        2561                  5       No                22                 4
## 578        7973                  3       No                14                 3
## 510       16280                  1       No                12                 3
## 687       22930                  0      Yes                12                 3
## 424       19305                  1       No                15                 3
## 379       26933                  0      Yes                18                 3
## 816        6311                  0       No                13                 3
## 108       25811                  4      Yes                18                 3
## 131        3356                  1      Yes                13                 3
## 343       21214                  4       No                15                 3
## 41        22577                  4       No                22                 4
## 627       15211                  1      Yes                12                 3
## 740       14004                  4       No                14                 3
## 298       22887                  1      Yes                24                 4
## 811       11012                  1       No                11                 3
## 258       12761                  7       No                14                 3
## 629       15813                  3       No                18                 3
## 859        6961                  2       No                21                 4
## 182       19461                  3       No                15                 3
## 305       26227                  4       No                24                 4
## 358       18300                  5       No                16                 3
## 696       13137                  1      Yes                18                 3
## 307       20165                  4       No                18                 3
## 827       19002                  2       No                13                 3
## 221       18686                  1       No                22                 4
## 736       26997                  0       No                14                 3
## 561       15062                  4       No                12                 3
## 313        4156                  1       No                12                 3
## 136        9931                  1       No                24                 4
## 794        8202                  1       No                13                 3
## 145       13888                  5       No                20                 4
## 123       19239                  4      Yes                12                 3
## 776       19630                  1       No                18                 3
## 234       17011                  2       No                14                 3
## 608       19191                  1      Yes                24                 4
## 495        6060                  1      Yes                13                 3
## 534       16542                  5       No                18                 3
## 803        5355                  1      Yes                14                 3
## 297       14074                  1       No                17                 3
## 208       11354                  7      Yes                19                 3
## 838       19921                  1       No                12                 3
## 569        7824                  7       No                17                 3
## 522        7324                  1      Yes                17                 3
## 248       18024                  0       No                14                 3
## 365        6992                  4       No                14                 3
## 665       10034                  0       No                20                 4
## 643       17323                  7       No                15                 3
## 595       25800                  1       No                13                 3
## 434       10007                  1       No                13                 3
## 757       19170                  1      Yes                25                 4
## 760        2493                  2      Yes                16                 3
## 218        2437                  3       No                11                 3
## 727       21222                  5       No                15                 3
## 508       15395                  2       No                11                 3
## 276       18575                  4       No                13                 3
## 169       22087                  3      Yes                12                 3
## 71        21412                  3       No                22                 4
## 573       19255                  1      Yes                12                 3
## 860       14075                  1       No                11                 3
## 485        3465                  1       No                12                 3
## 667        6599                  1       No                14                 3
## 460       22604                  1       No                16                 3
## 60         8040                  1      Yes                14                 3
## 449        5456                  1       No                11                 3
## 548       11983                  6       No                14                 3
## 19         5586                  0      Yes                14                 3
## 649       23016                  0       No                14                 3
## 638       22914                  1       No                18                 3
## 670       23474                  3       No                14                 3
## 319        3567                  3      Yes                12                 3
## 116        4814                  1      Yes                13                 3
## 840       13583                  4       No                12                 3
## 102        8386                  1       No                18                 3
## 214        4051                  9      Yes                13                 3
## 390        9150                  1      Yes                11                 3
## 597        9129                  3       No                16                 3
## 771        4317                  3       No                14                 3
## 160       23281                  3      Yes                17                 3
## 77        12288                  1      Yes                14                 3
## 529       26278                  1       No                18                 3
## 126       13586                  1      Yes                11                 3
## 262        7568                  6       No                13                 3
## 442       25412                  9       No                17                 3
## 642       10748                  2       No                12                 3
## 181       19588                  2       No                18                 3
## 163       20431                  0       No                12                 3
## 474        9752                  5       No                13                 3
## 228       12392                  1      Yes                16                 3
## 774       21777                  0      Yes                17                 3
## 646        8552                  7       No                11                 3
## 265       13257                  0       No                12                 3
## 427        7152                  1       No                13                 3
## 781       21728                  1      Yes                22                 4
## 249       13953                  3      Yes                14                 3
## 810       13364                  0      Yes                16                 3
## 40        21981                  0       No                12                 3
## 541       11309                  1       No                13                 3
## 497        9655                  3       No                21                 4
## 697        5602                  2       No                25                 4
## 865       14720                  4      Yes                18                 3
## 450       24162                  1       No                15                 3
## 600        3020                  2      Yes                16                 3
## 778       14947                  1       No                12                 3
## 363       25846                  1       No                15                 3
## 478        4267                  5       No                12                 3
## 403        5411                  4       No                12                 3
## 375       21082                  1       No                11                 3
## 335       21922                  9       No                21                 4
## 598       13436                  6       No                22                 4
## 142       26076                  1       No                12                 3
## 444        4167                  4      Yes                18                 3
## 741       24835                  2       No                18                 3
## 659       10110                  6      Yes                15                 3
## 790       18830                  1       No                18                 3
## 457       22589                  1       No                11                 3
## 188       21086                  6       No                14                 3
## 432        8532                  9       No                16                 3
## 488       15170                  1       No                17                 3
## 538       24017                  0      Yes                11                 3
## 752        8319                  1      Yes                11                 3
## 215       15174                  0       No                13                 3
## 540        2253                  7       No                13                 3
## 613       21509                  7       No                20                 4
## 730       19299                  0       No                14                 3
## 296       20232                  7      Yes                11                 3
## 328       11189                  6      Yes                17                 3
## 147        4673                  1       No                13                 3
## 701       15434                  1       No                11                 3
## 708       24609                  9       No                18                 3
## 84        17001                  4      Yes                13                 3
## 83        14284                  2       No                11                 3
## 250        5626                  7       No                16                 3
## 767       18863                  1       No                13                 3
## 281        6069                  1      Yes                17                 3
## 675       22490                  7       No                17                 3
## 843       19028                  3       No                22                 4
## 431        5242                  1      Yes                11                 3
## 30        26589                  0       No                18                 3
## 10        15332                  1       No                14                 3
## 817       20234                  5      Yes                24                 4
## 441        2338                  4      Yes                14                 3
## 820       23352                  3      Yes                11                 3
## 345       13192                  8       No                19                 3
## 592        7815                  0      Yes                23                 4
## 585       19121                  2      Yes                13                 3
## 660       22656                  1       No                13                 3
## 12        10494                  1       No                15                 3
## 293       11781                  1       No                16                 3
## 303       23737                  5       No                12                 3
## 738       16490                  5       No                17                 3
## 678       26849                  1       No                11                 3
## 338       22266                  0       No                17                 3
## 350       20420                  7       No                11                 3
## 720        8039                  0       No                17                 3
## 658       24456                  3       No                20                 4
## 107       26283                  1       No                13                 3
## 543       25326                  1      Yes                15                 3
## 518        8952                  8       No                22                 4
## 854        4824                  0       No                19                 3
## 43        24941                  4      Yes                16                 3
## 189       15815                  3       No                14                 3
## 171       25275                  7       No                23                 4
## 39         4022                  6       No                14                 3
## 216        8045                  2       No                14                 3
## 291       11005                  3       No                14                 3
## 58        16213                  1      Yes                18                 3
## 395        9068                  5      Yes                14                 3
## 856       16192                  1       No                13                 3
## 456        4349                  1       No                14                 3
## 22        18597                  3       No                12                 3
## 170       26968                  4       No                22                 4
## 588        6986                  7       No                23                 4
## 63         6393                  0       No                19                 3
## 676        9946                  2       No                14                 3
## 719       10414                  3      Yes                24                 4
## 417        7181                  0       No                14                 3
## 789       19805                  8       No                12                 3
## 70        15881                  1       No                12                 3
## 59        11677                  2      Yes                18                 3
## 800       26308                  6       No                20                 4
## 484       13939                  4      Yes                18                 3
## 203       19124                  1       No                12                 3
## 227       10910                  1       No                12                 3
## 243        4956                  0       No                23                 4
## 413       10227                  4       No                21                 4
## 577       11473                  4       No                14                 3
## 542        6076                  6       No                19                 3
## 476       20445                  4      Yes                21                 4
## 744       12862                  1       No                13                 3
## 804       10333                  0      Yes                22                 4
## 405       17852                  1       No                11                 3
## 397        2288                  6       No                13                 3
## 607       24668                  7       No                11                 3
## 501       12023                  7      Yes                14                 3
## 429        9571                  0      Yes                14                 3
## 205       20990                  2       No                11                 3
## 475       22482                  1       No                16                 3
## 104        8544                  2       No                16                 3
## 210       21196                  3      Yes                13                 3
## 471        6073                  1       No                11                 3
## 66        15053                  0      Yes                12                 3
## 88        10074                  1      Yes                24                 4
## 826       21445                  9       No                17                 3
## 601        7103                  1       No                13                 3
## 309       12992                  3      Yes                14                 3
## 737        8828                  0       No                11                 3
## 294       17231                  0       No                18                 3
## 421       17736                  1       No                15                 3
## 769       17433                  2       No                11                 3
## 430       23687                  6       No                13                 3
## 512        3449                  3       No                21                 4
## 361        5678                  0       No                14                 3
## 814        5220                  3       No                11                 3
## 480       15471                  1      Yes                25                 4
## 15        22957                  6       No                12                 3
## 486       19479                  8      Yes                11                 3
## 254       21495                  0       No                17                 3
## 491       25594                  9      Yes                11                 3
## 713       16620                  5       No                11                 3
## 178       15346                  6      Yes                14                 3
## 428       10531                  1       No                17                 3
## 691       14814                  3       No                11                 3
## 194       19658                  2       No                14                 3
## 599        5174                  1      Yes                20                 4
## 802        8346                  4      Yes                13                 3
## 378        2900                  3      Yes                12                 3
## 639       21630                  1      Yes                11                 3
## 155        6896                  1       No                14                 3
## 166       22052                  1       No                13                 3
## 207        9489                  8       No                13                 3
## 468       22002                  3       No                12                 3
## 105       19764                  4       No                12                 3
## 482       14871                  3      Yes                19                 3
## 587       15717                  7      Yes                12                 3
## 280       16143                  0      Yes                16                 3
## 440       19383                  0       No                13                 3
## 389        7439                  3       No                15                 3
## 499       16577                  6       No                13                 3
## 251       20439                  1       No                12                 3
## 231        5388                  1       No                19                 3
## 564       26862                  4       No                20                 4
## 640       16346                  0       No                11                 3
## 463        6645                  4       No                11                 3
## 100        3708                  5       No                17                 3
## 731       23814                  4       No                21                 4
## 141       18235                  4      Yes                12                 3
## 841       25233                  1       No                13                 3
## 745       13684                  0      Yes                22                 4
## 36        26062                  1       No                20                 4
## 792        5711                  2       No                15                 3
## 362       10642                  1       No                17                 3
## 86        21829                  3      Yes                13                 3
## 138       13943                  8       No                11                 3
## 344       22653                  1       No                20                 4
## 211        5640                  0       No                23                 4
## 461        9260                  4       No                17                 3
## 591       10293                  1      Yes                14                 3
## 829       15963                  4       No                14                 3
## 672        3921                  1       No                14                 3
## 653       13782                  9       No                17                 3
## 832       26820                  1      Yes                19                 3
## 371       11275                  1       No                12                 3
## 380       11539                  4      Yes                11                 3
## 97        11380                  8       No                12                 3
## 49         8059                  1      Yes                14                 3
## 469       21813                  8       No                18                 3
## 260        7298                  6      Yes                19                 3
## 650        3339                  3      Yes                14                 3
## 174       21708                  0      Yes                14                 3
## 775       18611                  2      Yes                14                 3
## 554        5543                  4       No                17                 3
## 723       20284                  5       No                14                 3
## 183       16090                  4       No                12                 3
## 347       15834                  2       No                11                 3
## 74         9051                  3      Yes                11                 3
## 641       13335                  1       No                22                 4
## 631        7975                  8       No                20                 4
## 118       23679                  4      Yes                13                 3
## 271       19665                  4       No                22                 4
## 551       19562                  1       No                12                 3
## 763       22074                  1       No                13                 3
## 357       23300                  1       No                19                 3
## 252       25952                  4       No                13                 3
## 619       21457                  4       No                15                 3
## 566       13422                  6      Yes                12                 3
## 459       10494                  2       No                22                 4
## 61         5518                  1      Yes                11                 3
## 179       15589                  1       No                14                 3
## 272       19332                  1       No                12                 3
## 76        10781                  1       No                23                 4
## 87        11825                  2       No                12                 3
## 224       12530                  1       No                14                 3
## 739        6179                  1       No                16                 3
## 164       23016                  3      Yes                13                 3
## 13        18869                  3       No                21                 4
## 526       23537                  2       No                12                 3
## 836       24666                  1       No                13                 3
## 693       17078                  3       No                23                 4
## 545        7530                  1       No                11                 3
## 334        6009                  1       No                11                 3
## 95        17053                  3       No                15                 3
## 657       15736                  5       No                16                 3
## 269       18079                  1       No                20                 4
## 53        19982                  1       No                13                 3
## 367       22534                  4       No                13                 3
## 420       21526                  1       No                18                 3
## 54        23163                  1       No                12                 3
## 383       24795                  4       No                11                 3
## 571       26841                  5       No                21                 4
## 274       13494                  4       No                13                 3
## 773        6420                  0       No                25                 4
## 168       22578                  4       No                19                 3
## 786        8847                  3       No                11                 3
## 546       20338                  1       No                12                 3
## 191       11934                  1       No                13                 3
## 572        8870                  1       No                19                 3
## 673       11827                  0       No                14                 3
## 67        19368                  1       No                13                 3
## 580        4204                  1      Yes                11                 3
## 869       20100                  4      Yes                19                 3
## 277       24440                  1       No                13                 3
## 828        6039                  0      Yes                12                 3
## 34        16340                  6       No                12                 3
## 504       10195                  1       No                11                 3
## 586       16523                  8      Yes                15                 3
## 562       21624                  2      Yes                14                 3
## 618        4009                  5      Yes                21                 4
## 615        9977                  5       No                11                 3
## 694        3427                  9      Yes                23                 4
## 127        4681                  1      Yes                22                 4
## 31        22812                  0       No                17                 3
## 793       14199                  3      Yes                19                 3
## 830        7999                  1       No                11                 3
## 308       22478                  3       No                17                 3
## 863        4652                  8      Yes                13                 3
## 68        13672                  1       No                13                 3
## 707       15696                  4       No                15                 3
## 807       12477                  2       No                11                 3
## 351       14842                  9       No                13                 3
## 582       15901                  2       No                14                 3
## 11        22539                  7       No                13                 3
## 149        6409                  8       No                22                 4
## 666       23060                  8      Yes                12                 3
## 857        8556                  5      Yes                11                 3
## 589       19106                  4       No                18                 3
## 349        4279                  2       No                13                 3
## 742       25291                  9       No                21                 4
## 648        6217                  1       No                15                 3
## 199        2094                  3       No                14                 3
## 624       16642                  1      Yes                16                 3
## 565       24375                  3       No                21                 4
## 310       15678                  0       No                22                 4
## 754       14011                  5       No                21                 4
## 604       26342                  1       No                13                 3
## 795       23793                  1      Yes                15                 3
## 519       23631                  0       No                12                 3
## 295       17381                  1      Yes                21                 4
## 558       22794                  1      Yes                13                 3
## 364        5949                  0       No                19                 3
## 408        6865                  1       No                14                 3
## 567       19737                  4       No                13                 3
## 235       19494                  1      Yes                12                 3
## 122       25479                  1      Yes                11                 3
## 628       15682                  0      Yes                14                 3
## 157        4258                  3       No                14                 3
## 819       11162                  0       No                13                 3
## 821       18783                  3       No                17                 3
## 120        6163                  1       No                11                 3
## 346       25098                  0       No                12                 3
## 539       21972                  1      Yes                16                 3
## 439        3810                  1      Yes                14                 3
## 256       24978                  4       No                13                 3
## 498       11411                  1      Yes                12                 3
## 679        9192                  7       No                13                 3
## 165        5100                  0       No                15                 3
## 352       12241                  4       No                11                 3
## 198       11879                  6       No                17                 3
## 353       21203                  3      Yes                13                 3
## 758       21534                  2       No                14                 3
## 852       16117                  1       No                13                 3
## 330       16616                  0       No                14                 3
## 152       21703                  1       No                12                 3
## 404       22792                  4       No                12                 3
## 384        9518                  3       No                13                 3
## 454       10410                  1       No                14                 3
## 418        7122                  4       No                18                 3
## 372        2890                  0       No                11                 3
## 106       13421                  1       No                22                 4
## 285        6004                  1       No                13                 3
## 23        19627                  3      Yes                13                 3
## 399       26236                  1       No                21                 4
## 465       15587                  9      Yes                16                 3
## 1          9250                  2       No                11                 3
## 583       24539                  3      Yes                16                 3
## 241        6950                  1      Yes                21                 4
## 51        14561                  3       No                17                 3
## 255       25178                  2       No                11                 3
## 470       26250                  1       No                11                 3
## 341       13072                  9      Yes                14                 3
## 45        16901                  1       No                22                 4
## 121       20335                  9       No                14                 3
## 507        9150                  1      Yes                13                 3
## 710        4544                  1       No                11                 3
## 348       26767                  1       No                20                 4
## 381       16375                  4       No                11                 3
## 201       17071                  4      Yes                16                 3
## 581        9075                  3       No                11                 3
## 517       18798                  1      Yes                18                 3
## 419        9961                  1       No                13                 3
## 772        2137                  1       No                25                 4
## 64         8018                  1       No                16                 3
## 223       16130                  1      Yes                25                 4
## 146       16928                  1       No                14                 3
## 25        12291                  0       No                14                 3
## 446       10205                  7       No                12                 3
## 448        5696                  5       No                18                 3
## 150       20460                  0       No                21                 4
## 782       20978                  1       No                11                 3
## 853       12682                  0      Yes                12                 3
## 766       23447                  1      Yes                14                 3
## 537       20619                  7       No                16                 3
## 2         17544                  1       No                14                 3
## 161       15998                  1      Yes                12                 3
## 75        21534                  9      Yes                19                 3
## 318       14120                  1       No                12                 3
## 414       26075                  8       No                13                 3
## 681       18154                  1       No                12                 3
## 186        2613                  1       No                23                 4
## 135        6227                  1       No                11                 3
## 732       17778                  4      Yes                18                 3
## 785        3536                  7       No                11                 3
## 770       17970                  1       No                13                 3
## 801        3193                  2       No                19                 3
## 779       11925                  1       No                20                 4
## 547       22477                  4       No                11                 3
## 278       10675                  0       No                19                 3
## 555       14242                  9       No                14                 3
## 263       22149                  5      Yes                13                 3
## 438       20006                  0       No                13                 3
## 206        7508                  1      Yes                13                 3
## 302       11031                  1       No                22                 4
## 192        8277                  2       No                14                 3
## 590       16002                  3      Yes                15                 3
## 834        7172                  1       No                25                 4
## 768       11373                  3       No                15                 3
## 733       19555                  1       No                12                 3
## 237       17312                  5       No                11                 3
## 321        3974                  6       No                20                 4
## 125       20260                  1       No                18                 3
## 784        4905                  1       No                12                 3
## 286       22949                  1      Yes                12                 3
## 682       15238                  7       No                20                 4
## 143       24208                  6       No                13                 3
## 275       13339                  8       No                11                 3
## 436        3415                  1       No                18                 3
## 156        6069                  7      Yes                12                 3
## 532       21447                  6       No                13                 3
## 842        9769                  1       No                13                 3
## 747        3157                  4      Yes                15                 3
## 866       18706                  1       No                11                 3
## 113       15322                  7       No                19                 3
## 535        4759                  1      Yes                11                 3
## 596       21816                  1       No                22                 4
## 162       12355                  1       No                12                 3
## 825       12421                  9      Yes                12                 3
## 728        5972                  1      Yes                17                 3
## 332       25812                  1       No                11                 3
## 702        5829                  1       No                20                 4
## 870       15986                  5       No                11                 3
## 636       26537                  1       No                13                 3
## 777       15428                  0       No                21                 4
## 128       23888                  0       No                13                 3
## 610       21437                  0       No                19                 3
## 818       25995                  0       No                11                 3
## 451       21653                  0      Yes                13                 3
## 712       22102                  3       No                12                 3
## 490        7360                  3       No                11                 3
## 222        5630                  2       No                14                 3
## 647       13556                  1       No                12                 3
## 85         2323                  9      Yes                11                 3
## 806       25949                  7      Yes                13                 3
## 516       16321                  5       No                18                 3
## 637       14399                  0       No                17                 3
## 159       11535                  8       No                11                 3
## 289       22952                  0       No                14                 3
## 635        9262                  8       No                16                 3
## 464        6670                  2       No                20                 4
## 654       23978                  3       No                21                 4
## 299       10322                  0      Yes                22                 4
## 788       17747                  2       No                15                 3
## 761       11479                  6      Yes                20                 4
## 664        9541                  1       No                20                 4
## 331       22384                  4       No                14                 3
## 204        3872                  7      Yes                13                 3
## 57        20366                  6      Yes                12                 3
## 29         5843                  6      Yes                13                 3
## 734       23914                  8       No                12                 3
## 55        20682                  1       No                23                 4
## 862       20364                  3       No                14                 3
## 279       26959                  1      Yes                11                 3
## 472       14753                  1      Yes                24                 4
## 190        8863                  1       No                15                 3
## 132        8191                  3       No                12                 3
## 409       22021                  2       No                16                 3
## 557       23428                  7       No                11                 3
## 340       19715                  1       No                13                 3
## 437       16374                  6       No                17                 3
## 844        5494                  0       No                11                 3
## 238       18089                  1      Yes                12                 3
## 329       18115                  1      Yes                16                 3
## 229       17519                  0       No                21                 4
## 423       20739                  4      Yes                18                 3
## 805       25043                  4       No                12                 3
## 656       22722                  1      Yes                13                 3
## 435       20652                  2       No                12                 3
## 492       22422                  4      Yes                11                 3
## 187        4973                  1       No                17                 3
## 575        7428                  1       No                20                 4
## 671       25258                  4       No                13                 3
## 560       20156                  1       No                17                 3
## 401       24793                  2       No                20                 4
## 176       25326                  1      Yes                11                 3
## 715       14229                  1       No                15                 3
## 621       19783                  1      Yes                18                 3
## 823        8978                  1       No                21                 4
## 815       12102                  0       No                19                 3
## 133        4386                  0       No                11                 3
## 425       24232                  1       No                11                 3
## 38         8658                  5      Yes                13                 3
## 692       10268                  1      Yes                12                 3
## 292        6927                  7       No                15                 3
## 690        7129                  5       No                13                 3
## 833       12449                  1       No                12                 3
## 503       11740                  2      Yes                11                 3
## 21        13934                  2      Yes                11                 3
## 112       13829                  2       No                15                 3
## 124        7791                  0       No                20                 4
## 422       23866                  3      Yes                15                 3
## 91        12106                  1      Yes                23                 4
## 259       24444                  2      Yes                13                 3
## 453       13492                  1      Yes                18                 3
## 35        10138                  8       No                24                 4
## 17        13554                  1       No                12                 3
## 677       23361                  0       No                15                 3
## 415       12253                  0       No                16                 3
## 813        5915                  1      Yes                12                 3
## 32        13637                  1       No                18                 3
## 320       21221                  1      Yes                12                 3
## 496        5594                  2       No                14                 3
## 225       14293                  2       No                19                 3
## 226        4077                  1       No                13                 3
## 385       10332                  9      Yes                12                 3
## 700       10849                  5       No                11                 3
## 411        8635                  0       No                21                 4
## 822       10732                  2       No                14                 3
## 393        3995                  1      Yes                13                 3
## 799        6148                  1      Yes                25                 4
## 324       21029                  8      Yes                23                 4
## 267       11929                  7       No                14                 3
## 698        9945                  8       No                16                 3
## 264       18203                  1       No                15                 3
## 110       11288                  1       No                14                 3
## 494       21195                  1       No                19                 3
## 42        12388                  0       No                13                 3
## 245       17689                  1      Yes                15                 3
## 489       19294                  9      Yes                13                 3
## 300       24737                  5      Yes                13                 3
## 652       10893                  0      Yes                18                 3
## 688       13248                  6       No                21                 4
## 94         4223                  3      Yes                16                 3
## 377        8269                  1       No                16                 3
## 467       17001                  3      Yes                21                 4
## 394        2845                  4       No                19                 3
## 445       14218                  7      Yes                17                 3
## 524        2125                  1      Yes                17                 3
## 680       11737                  3       No                15                 3
## 253        6153                  1       No                14                 3
## 177       21199                  5      Yes                13                 3
## 500        3987                  6       No                19                 3
## 506       15624                  3       No                12                 3
## 858       14034                  1       No                24                 4
## 549       26707                  3       No                17                 3
## 674       16612                  1      Yes                19                 3
## 443       14935                  2       No                11                 3
## 14        17434                  1       No                18                 3
## 333       11092                  1      Yes                12                 3
## 663        5596                  4      Yes                12                 3
## 530        4510                  9      Yes                18                 3
## 3         19944                  2       No                11                 3
## 523       18787                  2       No                17                 3
## 369       12826                  2       No                16                 3
## 129       20003                  1      Yes                14                 3
## 633        4981                  8      Yes                12                 3
## 48         5569                  0      Yes                14                 3
## 325        7060                  1       No                16                 3
## 845       25353                  5       No                12                 3
## 7          5561                  2      Yes                12                 3
## 847       16102                  1       No                14                 3
## 716       11585                  1       No                11                 3
## 28        18385                  0      Yes                17                 3
## 230       11652                  2      Yes                19                 3
## 416       24442                  2       No                14                 3
## 373       20308                  1       No                18                 3
## 809        3811                  1       No                12                 3
## 729       23213                  1      Yes                18                 3
## 812        4910                  4       No                11                 3
## 528       17089                  1      Yes                12                 3
## 37        21530                  9       No                17                 3
## 705       25657                  8       No                17                 3
## 354        8841                  3      Yes                18                 3
## 563       12086                  9       No                14                 3
## 559       11806                  1       No                13                 3
## 525        8456                  3       No                17                 3
## 868       24200                  3      Yes                17                 3
## 27        12355                  0       No                11                 3
## 755       24001                  9       No                12                 3
## 594       22102                  1       No                14                 3
## 520       10261                  1       No                16                 3
## 287       26092                  1      Yes                23                 4
## 620       16900                  1       No                18                 3
## 753       20689                  2      Yes                15                 3
## 65         3372                  1       No                13                 3
## 154       15530                  3       No                12                 3
## 662        8416                  3       No                12                 3
## 247       25713                  1      Yes                14                 3
## 850        7102                  0       No                18                 3
## 33        14977                  3      Yes                12                 3
## 550        8318                  1       No                16                 3
## 797        7501                  0      Yes                14                 3
## 509        2539                  4       No                17                 3
## 24        21602                  7       No                13                 3
## 185       17872                  1       No                11                 3
## 513       17360                  6       No                13                 3
## 553        4223                  1       No                21                 4
## 455       17997                  7       No                11                 3
## 477       24558                  4       No                19                 3
## 360       20251                  0       No                11                 3
## 846       13535                  1       No                12                 3
## 217       22174                  3       No                19                 3
## 765        2243                  0       No                19                 3
## 714        7246                  4       No                11                 3
## 593       15747                  3       No                15                 3
## 699       18420                  1      Yes                12                 3
## 762       12982                  1      Yes                11                 3
## 824        6233                  1       No                12                 3
## 407       13402                  1       No                14                 3
## 391       13305                  5       No                17                 3
## 153       16985                  1       No                14                 3
## 433       22710                  3       No                20                 4
## 82         5151                  2       No                16                 3
## 831       14039                  1      Yes                15                 3
## 232        9687                  1       No                13                 3
## 796        3164                  1      Yes                11                 3
## 685        6672                  1       No                11                 3
## 317       11314                  6       No                18                 3
## 242       13035                  3       No                22                 4
## 290       20317                  1       No                16                 3
## 119        4609                  4       No                12                 3
## 808       11992                  1       No                24                 4
## 6          4809                  1       No                21                 4
## 311       13008                  9       No                17                 3
## 392       21436                  7      Yes                19                 3
## 481        6225                  0       No                12                 3
## 114        4761                  2       No                11                 3
## 864       10225                  9      Yes                12                 3
## 683        7419                  6       No                14                 3
## 368       19345                  0       No                12                 3
## 622        6759                  1      Yes                19                 3
## 314       13983                  2       No                17                 3
## 306       10778                  0       No                17                 3
## 412       15869                  1       No                12                 3
## 219       23910                  1       No                14                 3
##     RelationshipSatisfaction StandardHours StockOptionLevel TotalWorkingYears
## 284                        4            80                3                13
## 848                        1            80                3                19
## 101                        2            80                0                 6
## 623                        3            80                0                10
## 645                        1            80                1                 5
## 400                        2            80                0                16
## 98                         4            80                1                17
## 103                        1            80                1                 6
## 726                        4            80                2                 5
## 602                        2            80                1                 9
## 326                        3            80                0                 1
## 79                         4            80                0                23
## 270                        3            80                1                 7
## 382                        4            80                1                 8
## 184                        4            80                0                 9
## 574                        3            80                2                10
## 4                          3            80                2                14
## 661                        4            80                2                10
## 552                        4            80                1                 6
## 212                        2            80                0                21
## 195                        4            80                0                 5
## 511                        3            80                1                10
## 479                        3            80                0                12
## 605                        3            80                0                 2
## 634                        1            80                1                 7
## 578                        4            80                0                 7
## 510                        4            80                0                23
## 687                        1            80                0                 9
## 424                        3            80                0                 0
## 379                        1            80                1                 6
## 816                        2            80                1                15
## 108                        1            80                1                35
## 131                        2            80                1                10
## 343                        3            80                1                 9
## 41                         4            80                1                37
## 627                        3            80                2                 5
## 740                        4            80                0                 9
## 298                        4            80                0                 9
## 811                        3            80                2                12
## 258                        2            80                2                 8
## 629                        2            80                1                23
## 859                        4            80                1                 7
## 182                        4            80                1                11
## 305                        1            80                0                 7
## 358                        2            80                0                 6
## 696                        1            80                0                 3
## 307                        2            80                0                 8
## 827                        1            80                3                10
## 221                        3            80                0                 6
## 736                        2            80                0                 9
## 561                        3            80                0                13
## 313                        1            80                0                 7
## 136                        4            80                1                 8
## 794                        2            80                3                17
## 145                        2            80                3                15
## 123                        3            80                1                18
## 776                        4            80                0                 2
## 234                        4            80                1                16
## 608                        3            80                1                 8
## 495                        1            80                1                10
## 534                        2            80                1                 9
## 803                        4            80                0                21
## 297                        3            80                0                10
## 208                        2            80                0                17
## 838                        4            80                0                10
## 569                        1            80                0                10
## 522                        3            80                3                 1
## 248                        2            80                1                 3
## 365                        4            80                1                23
## 665                        3            80                0                10
## 643                        2            80                0                31
## 595                        4            80                2                18
## 434                        3            80                1                 1
## 757                        4            80                1                10
## 760                        1            80                0                26
## 218                        2            80                1                24
## 727                        2            80                1                10
## 508                        2            80                0                14
## 276                        4            80                1                28
## 169                        2            80                2                18
## 71                         1            80                1                12
## 573                        3            80                1                 7
## 860                        4            80                1                10
## 485                        4            80                1                40
## 667                        4            80                1                11
## 460                        3            80                0                10
## 60                         4            80                0                 1
## 449                        4            80                0                10
## 548                        4            80                0                10
## 19                         1            80                3                 6
## 649                        2            80                0                16
## 638                        3            80                1                 9
## 670                        1            80                0                36
## 319                        4            80                2                 8
## 116                        4            80                0                10
## 840                        4            80                0                29
## 102                        1            80                1                13
## 214                        4            80                1                 8
## 390                        3            80                0                 3
## 597                        1            80                0                16
## 771                        3            80                0                 9
## 160                        3            80                0                20
## 77                         4            80                0                10
## 529                        1            80                0                 6
## 126                        4            80                0                10
## 262                        3            80                0                11
## 442                        3            80                1                 9
## 642                        2            80                1                15
## 181                        2            80                1                15
## 163                        4            80                0                 6
## 474                        2            80                0                 9
## 228                        1            80                1                 4
## 774                        1            80                1                 2
## 646                        1            80                1                15
## 265                        3            80                1                 6
## 427                        2            80                2                 1
## 781                        4            80                0                 4
## 249                        1            80                2                12
## 810                        4            80                1                 6
## 40                         1            80                1                 3
## 541                        1            80                3                10
## 497                        4            80                2                 8
## 697                        2            80                1                23
## 865                        4            80                2                10
## 450                        1            80                1                10
## 600                        1            80                1                 6
## 778                        3            80                3                 1
## 363                        4            80                1                33
## 478                        1            80                2                 8
## 403                        3            80                0                 7
## 375                        1            80                0                 2
## 335                        4            80                1                30
## 598                        2            80                1                20
## 142                        4            80                2                 2
## 444                        1            80                3                 8
## 741                        4            80                0                 6
## 659                        4            80                0                 8
## 790                        4            80                0                 2
## 457                        1            80                2                10
## 188                        3            80                3                29
## 432                        2            80                1                 6
## 488                        4            80                1                 5
## 538                        3            80                1                 4
## 752                        1            80                0                 3
## 215                        4            80                0                 5
## 540                        4            80                0                 9
## 613                        1            80                0                13
## 730                        3            80                1                 3
## 296                        3            80                1                 5
## 328                        3            80                1                 9
## 147                        4            80                1                 8
## 701                        4            80                0                 1
## 708                        4            80                0                 8
## 84                         1            80                2                13
## 83                         4            80                1                10
## 250                        2            80                1                22
## 767                        3            80                0                10
## 281                        1            80                1                10
## 675                        1            80                0                 5
## 843                        3            80                0                31
## 431                        1            80                0                 5
## 30                         1            80                1                 5
## 10                         2            80                1                 8
## 817                        2            80                0                12
## 441                        4            80                0                10
## 820                        4            80                0                 6
## 345                        3            80                3                 8
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## 585                        4            80                0                 9
## 660                        3            80                0                 6
## 12                         2            80                1                 3
## 293                        4            80                0                 7
## 303                        4            80                1                 8
## 738                        4            80                0                13
## 678                        1            80                1                10
## 338                        3            80                0                 7
## 350                        3            80                0                30
## 720                        2            80                3                10
## 658                        1            80                1                26
## 107                        1            80                1                10
## 543                        4            80                1                 1
## 518                        2            80                3                 7
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## 43                         2            80                1                17
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## 171                        4            80                1                10
## 39                         1            80                0                36
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## 63                         3            80                1                 3
## 676                        3            80                1                26
## 719                        1            80                0                13
## 417                        3            80                0                12
## 789                        2            80                3                34
## 70                         2            80                0                17
## 59                         1            80                2                15
## 800                        1            80                1                13
## 484                        3            80                1                19
## 203                        3            80                1                14
## 227                        3            80                1                 1
## 243                        4            80                1                 6
## 413                        1            80                0                 8
## 577                        1            80                0                20
## 542                        2            80                1                14
## 476                        3            80                0                14
## 744                        3            80                0                 3
## 804                        1            80                0                 9
## 405                        4            80                0                 6
## 397                        3            80                0                26
## 607                        4            80                0                20
## 501                        4            80                0                31
## 429                        4            80                0                 4
## 205                        1            80                1                 6
## 475                        4            80                1                 4
## 104                        1            80                1                 5
## 210                        3            80                1                12
## 471                        3            80                1                 6
## 66                         4            80                2                 7
## 88                         4            80                1                 5
## 826                        4            80                2                23
## 601                        3            80                1                 1
## 309                        4            80                2                17
## 737                        1            80                1                21
## 294                        1            80                2                14
## 421                        3            80                0                 5
## 769                        3            80                1                12
## 430                        2            80                1                13
## 512                        2            80                1                13
## 361                        1            80                1                34
## 814                        3            80                1                27
## 480                        1            80                1                16
## 15                         3            80                0                10
## 486                        1            80                0                 8
## 254                        3            80                0                 2
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## 178                        2            80                1                 6
## 428                        1            80                0                 3
## 691                        3            80                0                10
## 194                        1            80                1                14
## 599                        2            80                1                 6
## 802                        3            80                0                10
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## 155                        2            80                2                 1
## 166                        4            80                0                 2
## 207                        2            80                0                 7
## 468                        2            80                0                 5
## 105                        2            80                0                35
## 482                        2            80                1                 8
## 587                        4            80                3                17
## 280                        2            80                0                 4
## 440                        3            80                0                10
## 389                        3            80                0                17
## 499                        2            80                2                17
## 251                        3            80                3                 1
## 231                        1            80                2                10
## 564                        3            80                1                13
## 640                        2            80                1                 5
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## 100                        1            80                1                 7
## 731                        3            80                1                 4
## 141                        1            80                1                33
## 841                        3            80                0                 0
## 745                        2            80                1                 6
## 36                         3            80                0                 5
## 792                        4            80                0                 9
## 362                        4            80                0                 1
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## 138                        3            80                1                22
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## 829                        2            80                1                 9
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## 832                        4            80                0                 0
## 371                        3            80                1                 4
## 380                        2            80                0                 7
## 97                         4            80                1                23
## 49                         4            80                0                 0
## 469                        4            80                0                 7
## 260                        3            80                1                 7
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## 174                        4            80                2                10
## 775                        3            80                1                24
## 554                        1            80                2                13
## 723                        3            80                2                10
## 183                        4            80                0                18
## 347                        4            80                0                 5
## 74                         1            80                1                 6
## 641                        2            80                1                 1
## 631                        2            80                1                19
## 118                        1            80                1                10
## 271                        2            80                2                10
## 551                        2            80                1                22
## 763                        1            80                0                19
## 357                        3            80                0                 5
## 252                        4            80                2                12
## 619                        1            80                1                 9
## 566                        3            80                0                 6
## 459                        4            80                1                 5
## 61                         1            80                1                16
## 179                        4            80                0                 9
## 272                        3            80                1                11
## 76                         4            80                0                12
## 87                         4            80                0                20
## 224                        4            80                1                 1
## 739                        2            80                0                 5
## 164                        3            80                0                10
## 13                         2            80                0                17
## 526                        1            80                1                30
## 836                        4            80                1                 9
## 693                        2            80                0                14
## 545                        3            80                0                 6
## 334                        4            80                0                 9
## 95                         2            80                0                21
## 657                        4            80                2                16
## 269                        3            80                3                 9
## 53                         4            80                1                10
## 367                        3            80                2                15
## 420                        3            80                0                10
## 54                         2            80                0                 9
## 383                        1            80                3                15
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## 274                        1            80                2                11
## 773                        4            80                0                20
## 168                        3            80                1                10
## 786                        3            80                0                 9
## 546                        2            80                0                10
## 191                        4            80                2                11
## 572                        1            80                0                 1
## 673                        4            80                0                 5
## 67                         2            80                0                17
## 580                        2            80                2                 6
## 869                        3            80                1                 7
## 277                        4            80                1                 2
## 828                        4            80                0                 4
## 34                         2            80                1                10
## 504                        3            80                1                10
## 586                        3            80                1                15
## 562                        2            80                0                23
## 618                        3            80                1                 9
## 615                        1            80                1                10
## 694                        3            80                0                 3
## 127                        2            80                0                10
## 31                         4            80                3                 9
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##     TrainingTimesLastYear WorkLifeBalance YearsAtCompany YearsInCurrentRole
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SalaryTest = Attritiondata[-TrainObs,]
SalaryTest
##      ID Age Attrition    BusinessTravel DailyRate             Department
## 5     5  24        No Travel_Frequently       567 Research & Development
## 8     8  37        No     Travel_Rarely       309                  Sales
## 9     9  34        No     Travel_Rarely      1333                  Sales
## 16   16  31        No        Non-Travel      1188                  Sales
## 18   18  46        No        Non-Travel      1144 Research & Development
## 20   20  44        No     Travel_Rarely       170 Research & Development
## 26   26  44        No     Travel_Rarely      1099                  Sales
## 44   44  42        No     Travel_Rarely      1059 Research & Development
## 46   46  42        No Travel_Frequently       748 Research & Development
## 47   47  32       Yes     Travel_Rarely       964                  Sales
## 50   50  27        No        Non-Travel       691 Research & Development
## 52   52  58        No     Travel_Rarely      1055 Research & Development
## 56   56  41        No     Travel_Rarely       548 Research & Development
## 62   62  36        No     Travel_Rarely       325 Research & Development
## 69   69  35        No Travel_Frequently       664 Research & Development
## 72   72  28        No     Travel_Rarely       866                  Sales
## 73   73  35       Yes     Travel_Rarely       556 Research & Development
## 78   78  46        No     Travel_Rarely       563                  Sales
## 80   80  31        No     Travel_Rarely      1276 Research & Development
## 81   81  37       Yes     Travel_Rarely      1141 Research & Development
## 89   89  27        No Travel_Frequently       994                  Sales
## 90   90  46        No     Travel_Rarely       705                  Sales
## 92   92  29       Yes     Travel_Rarely       408                  Sales
## 93   93  37       Yes     Travel_Rarely      1373 Research & Development
## 96   96  42        No     Travel_Rarely       635                  Sales
## 99   99  29        No Travel_Frequently       410 Research & Development
## 109 109  46       Yes     Travel_Rarely       261 Research & Development
## 111 111  28        No Travel_Frequently       773 Research & Development
## 115 115  35        No     Travel_Rarely      1361                  Sales
## 117 117  25        No     Travel_Rarely      1356                  Sales
## 130 130  46        No     Travel_Rarely      1319                  Sales
## 134 134  39        No     Travel_Rarely       492 Research & Development
## 137 137  29       Yes     Travel_Rarely       805 Research & Development
## 139 139  39       Yes     Travel_Rarely      1122 Research & Development
## 140 140  37        No     Travel_Rarely      1189                  Sales
## 144 144  37        No     Travel_Rarely       228                  Sales
## 148 148  33        No     Travel_Rarely      1242                  Sales
## 151 151  31       Yes     Travel_Rarely      1365                  Sales
## 158 158  39       Yes Travel_Frequently       203 Research & Development
## 167 167  49        No     Travel_Rarely       301 Research & Development
## 172 172  47        No        Non-Travel      1169 Research & Development
## 173 173  46        No Travel_Frequently      1034 Research & Development
## 175 175  53        No     Travel_Rarely      1376                  Sales
## 180 180  38        No     Travel_Rarely       702                  Sales
## 193 193  46        No     Travel_Rarely      1485 Research & Development
## 196 196  51        No     Travel_Rarely       833 Research & Development
## 197 197  51        No     Travel_Rarely       432 Research & Development
## 200 200  24        No     Travel_Rarely       823 Research & Development
## 202 202  32        No     Travel_Rarely       548 Research & Development
## 209 209  30        No     Travel_Rarely       201 Research & Development
## 213 213  37        No     Travel_Rarely      1225 Research & Development
## 220 220  26        No     Travel_Rarely       583 Research & Development
## 233 233  47       Yes Travel_Frequently      1093                  Sales
## 236 236  37       Yes     Travel_Rarely       625                  Sales
## 239 239  25        No     Travel_Rarely       309        Human Resources
## 240 240  50        No     Travel_Rarely       813 Research & Development
## 244 244  25       Yes     Travel_Rarely       383                  Sales
## 246 246  29        No     Travel_Rarely      1086 Research & Development
## 257 257  31        No Travel_Frequently       444                  Sales
## 261 261  31       Yes Travel_Frequently       703                  Sales
## 266 266  35        No     Travel_Rarely       809 Research & Development
## 268 268  32       Yes     Travel_Rarely      1259 Research & Development
## 273 273  27        No     Travel_Rarely       728                  Sales
## 282 282  41        No     Travel_Rarely       263 Research & Development
## 283 283  40        No     Travel_Rarely      1194 Research & Development
## 288 288  34        No     Travel_Rarely      1346 Research & Development
## 301 301  32        No Travel_Frequently       379                  Sales
## 304 304  35        No     Travel_Rarely      1395 Research & Development
## 312 312  40        No     Travel_Rarely       302 Research & Development
## 315 315  60        No     Travel_Rarely      1179                  Sales
## 316 316  47        No     Travel_Rarely       955                  Sales
## 322 322  34        No     Travel_Rarely      1397 Research & Development
## 323 323  30        No Travel_Frequently      1012 Research & Development
## 327 327  44        No     Travel_Rarely      1313 Research & Development
## 336 336  33       Yes Travel_Frequently       827 Research & Development
## 337 337  35        No Travel_Frequently      1182                  Sales
## 339 339  50       Yes Travel_Frequently       959                  Sales
## 342 342  28        No Travel_Frequently       193 Research & Development
## 355 355  41        No     Travel_Rarely       796                  Sales
## 356 356  34        No     Travel_Rarely      1326                  Sales
## 359 359  32        No     Travel_Rarely       427 Research & Development
## 366 366  56        No Travel_Frequently       906                  Sales
## 370 370  32        No     Travel_Rarely      1018 Research & Development
## 374 374  37        No     Travel_Rarely      1470 Research & Development
## 376 376  50        No Travel_Frequently       333 Research & Development
## 386 386  38        No     Travel_Rarely      1333 Research & Development
## 387 387  35        No Travel_Frequently       944                  Sales
## 388 388  29        No     Travel_Rarely       232 Research & Development
## 396 396  31        No     Travel_Rarely       192 Research & Development
## 398 398  34       Yes     Travel_Rarely      1107        Human Resources
## 402 402  42        No        Non-Travel       926 Research & Development
## 406 406  43        No     Travel_Rarely       782 Research & Development
## 410 410  43        No     Travel_Rarely       589 Research & Development
## 426 426  43        No     Travel_Rarely       415                  Sales
## 447 447  38        No Travel_Frequently      1189 Research & Development
## 452 452  44        No     Travel_Rarely      1467 Research & Development
## 458 458  51        No     Travel_Rarely       632                  Sales
## 462 462  36        No     Travel_Rarely       311 Research & Development
## 466 466  38        No     Travel_Rarely       371 Research & Development
## 473 473  45        No     Travel_Rarely       193 Research & Development
## 483 483  34        No Travel_Frequently       735 Research & Development
## 487 487  30       Yes     Travel_Rarely       945                  Sales
## 493 493  29        No     Travel_Rarely       469                  Sales
## 502 502  28       Yes     Travel_Rarely       103 Research & Development
## 505 505  47        No     Travel_Rarely       359 Research & Development
## 514 514  33        No Travel_Frequently       515 Research & Development
## 515 515  21        No        Non-Travel       895                  Sales
## 521 521  34        No Travel_Frequently       702 Research & Development
## 527 527  45        No     Travel_Rarely      1268                  Sales
## 531 531  38        No     Travel_Rarely       330 Research & Development
## 533 533  29        No     Travel_Rarely      1252 Research & Development
## 536 536  43        No        Non-Travel      1344 Research & Development
## 544 544  38        No     Travel_Rarely      1261 Research & Development
## 556 556  37        No     Travel_Rarely       558                  Sales
## 568 568  30       Yes     Travel_Rarely       740                  Sales
## 570 570  50        No     Travel_Rarely       939 Research & Development
## 576 576  37        No     Travel_Rarely      1115 Research & Development
## 579 579  39        No Travel_Frequently       711 Research & Development
## 584 584  28        No     Travel_Rarely       760                  Sales
## 603 603  30        No     Travel_Rarely       153 Research & Development
## 606 606  53        No     Travel_Rarely       970 Research & Development
## 609 609  26        No     Travel_Rarely       652 Research & Development
## 611 611  35        No     Travel_Rarely       817 Research & Development
## 612 612  41        No        Non-Travel       509 Research & Development
## 614 614  19       Yes     Travel_Rarely       419                  Sales
## 616 616  34        No     Travel_Rarely      1157 Research & Development
## 617 617  33        No     Travel_Rarely      1099 Research & Development
## 625 625  28       Yes Travel_Frequently       289 Research & Development
## 626 626  27        No     Travel_Rarely      1167 Research & Development
## 630 630  34        No     Travel_Rarely      1442 Research & Development
## 632 632  34        No     Travel_Rarely       937                  Sales
## 644 644  34       Yes        Non-Travel       967 Research & Development
## 651 651  35        No     Travel_Rarely       992 Research & Development
## 655 655  22       Yes Travel_Frequently      1368 Research & Development
## 668 668  33       Yes     Travel_Rarely       587 Research & Development
## 669 669  32       Yes     Travel_Rarely      1089 Research & Development
## 684 684  57        No     Travel_Rarely       334 Research & Development
## 686 686  31        No     Travel_Rarely      1274 Research & Development
## 689 689  19       Yes     Travel_Rarely       303 Research & Development
## 695 695  37        No Travel_Frequently      1278                  Sales
## 703 703  35        No        Non-Travel      1212                  Sales
## 704 704  26       Yes     Travel_Rarely       920        Human Resources
## 706 706  41        No        Non-Travel       267                  Sales
## 709 709  38        No     Travel_Rarely      1153 Research & Development
## 711 711  30        No     Travel_Rarely       634 Research & Development
## 717 717  30        No     Travel_Rarely       852                  Sales
## 718 718  28        No     Travel_Rarely       857 Research & Development
## 721 721  37        No     Travel_Rarely       482 Research & Development
## 722 722  37        No     Travel_Rarely       671 Research & Development
## 724 724  36        No     Travel_Rarely       796 Research & Development
## 725 725  42        No     Travel_Rarely      1142 Research & Development
## 735 735  34        No     Travel_Rarely       479 Research & Development
## 743 743  37        No     Travel_Rarely       674 Research & Development
## 746 746  24        No     Travel_Rarely       350 Research & Development
## 748 748  34        No Travel_Frequently       669 Research & Development
## 749 749  24        No     Travel_Rarely       506 Research & Development
## 750 750  33        No     Travel_Rarely       134 Research & Development
## 751 751  20       Yes Travel_Frequently       769                  Sales
## 756 756  44        No        Non-Travel       381 Research & Development
## 759 759  38        No     Travel_Rarely      1495 Research & Development
## 764 764  50        No        Non-Travel       145                  Sales
## 780 780  29       Yes     Travel_Rarely      1092 Research & Development
## 783 783  33        No     Travel_Rarely      1075        Human Resources
## 787 787  51        No     Travel_Rarely       942 Research & Development
## 791 791  49        No     Travel_Rarely       271 Research & Development
## 798 798  22       Yes     Travel_Rarely      1294 Research & Development
## 835 835  55        No        Non-Travel       177 Research & Development
## 837 837  37        No     Travel_Rarely      1439 Research & Development
## 839 839  47        No     Travel_Rarely      1001 Research & Development
## 849 849  40       Yes     Travel_Rarely       575                  Sales
## 851 851  31       Yes     Travel_Rarely       542                  Sales
## 855 855  35        No     Travel_Rarely       219 Research & Development
## 861 861  51        No Travel_Frequently       968 Research & Development
## 867 867  32        No        Non-Travel       976                  Sales
##     DistanceFromHome Education   EducationField EmployeeCount EmployeeNumber
## 5                  2         1 Technical Degree             1           1646
## 8                 10         4    Life Sciences             1           1105
## 9                 10         4    Life Sciences             1           1055
## 16                20         2        Marketing             1            947
## 18                 7         4          Medical             1            487
## 20                 1         4    Life Sciences             1           1903
## 26                 5         3        Marketing             1           1267
## 44                 9         2            Other             1           1595
## 46                 9         2          Medical             1           1480
## 47                 1         2    Life Sciences             1           1734
## 50                 9         3          Medical             1            218
## 52                 1         3          Medical             1           1423
## 56                 9         4    Life Sciences             1           1772
## 62                10         4 Technical Degree             1           1312
## 69                 1         3          Medical             1             88
## 72                 5         3          Medical             1           1469
## 73                23         2    Life Sciences             1            261
## 78                 1         4    Life Sciences             1           1602
## 80                 2         1          Medical             1           1974
## 81                11         2          Medical             1           1033
## 89                 8         3    Life Sciences             1             56
## 90                 2         4        Marketing             1             38
## 92                23         1    Life Sciences             1           1165
## 93                 2         2            Other             1              4
## 96                 1         1    Life Sciences             1            387
## 99                 2         1    Life Sciences             1           1513
## 109               21         2          Medical             1           1821
## 111                6         3    Life Sciences             1           1154
## 115               17         4    Life Sciences             1           1218
## 117               10         4    Life Sciences             1           1240
## 130                3         3 Technical Degree             1           1863
## 134               12         3          Medical             1           1654
## 137                1         2    Life Sciences             1            816
## 139                6         3          Medical             1            932
## 140                3         3    Life Sciences             1            152
## 144                6         4          Medical             1            378
## 148                8         4    Life Sciences             1           1560
## 151               13         4          Medical             1            650
## 158                2         3    Life Sciences             1           1127
## 167               22         4            Other             1           1655
## 172               14         4 Technical Degree             1           1934
## 173               18         1          Medical             1            624
## 175                2         2          Medical             1            981
## 180                1         4    Life Sciences             1            230
## 193               18         3          Medical             1            550
## 196                1         3    Life Sciences             1            353
## 197                9         4    Life Sciences             1            116
## 200               17         2            Other             1            643
## 202                1         3    Life Sciences             1             96
## 209                5         3 Technical Degree             1            197
## 213               10         2    Life Sciences             1            715
## 220                4         2    Life Sciences             1           1275
## 233                9         3    Life Sciences             1           1716
## 236                1         4    Life Sciences             1            970
## 239                2         3  Human Resources             1           1987
## 240               17         5    Life Sciences             1           1656
## 244                9         2    Life Sciences             1           1439
## 246                7         1          Medical             1            912
## 257                5         3        Marketing             1            399
## 261                2         3    Life Sciences             1           1379
## 266               16         3          Medical             1             14
## 268                2         4    Life Sciences             1           1692
## 273               23         1          Medical             1           1864
## 282                6         3          Medical             1            957
## 283                1         3    Life Sciences             1           1822
## 288               19         2          Medical             1             18
## 301                5         2    Life Sciences             1            889
## 304                9         4          Medical             1           2008
## 312                6         3    Life Sciences             1            601
## 315               16         4        Marketing             1            732
## 316                4         2    Life Sciences             1           1003
## 322                1         5    Life Sciences             1            683
## 323                5         4    Life Sciences             1            861
## 327                7         3          Medical             1           1608
## 336               29         4          Medical             1           1101
## 337               11         2        Marketing             1           1137
## 339                1         4            Other             1           1113
## 342                2         3    Life Sciences             1           1296
## 355                4         1        Marketing             1           1815
## 356                3         3            Other             1           1478
## 359                1         3          Medical             1             78
## 366                6         3    Life Sciences             1            532
## 370                2         4          Medical             1            439
## 374               10         3          Medical             1           1640
## 376               22         5          Medical             1           1539
## 386                1         3 Technical Degree             1            950
## 387                1         3        Marketing             1            314
## 388               19         3 Technical Degree             1            611
## 396                2         4    Life Sciences             1            426
## 398                9         4 Technical Degree             1           1467
## 402               21         2          Medical             1            270
## 406                6         4            Other             1            661
## 410               14         2    Life Sciences             1            843
## 426               25         3          Medical             1           1076
## 447                1         3    Life Sciences             1           1668
## 452               20         3    Life Sciences             1           1475
## 458               21         4        Marketing             1            120
## 462                7         3    Life Sciences             1           1659
## 466                2         3    Life Sciences             1             24
## 473                6         4            Other             1            101
## 483               22         4            Other             1           1932
## 487                9         3          Medical             1           1876
## 493               10         3          Medical             1           1650
## 502               24         3    Life Sciences             1             19
## 505                2         4          Medical             1           1443
## 514                1         2    Life Sciences             1             73
## 515                9         2          Medical             1            484
## 521               16         4    Life Sciences             1            838
## 527                4         2    Life Sciences             1            240
## 531               17         1    Life Sciences             1           1088
## 533               23         2    Life Sciences             1            824
## 536                7         3          Medical             1            262
## 544                2         4    Life Sciences             1            271
## 556                2         3        Marketing             1            656
## 568                1         3    Life Sciences             1           1562
## 570               24         3    Life Sciences             1           1005
## 576                1         4    Life Sciences             1             77
## 579                4         3          Medical             1           1633
## 584                2         4        Marketing             1            846
## 603                8         2    Life Sciences             1           1015
## 606                7         3    Life Sciences             1            730
## 609                7         3            Other             1           1417
## 611                1         3          Medical             1           1369
## 612                2         4            Other             1            616
## 614               21         3            Other             1            959
## 616                5         2          Medical             1           1696
## 617                4         4          Medical             1           1502
## 625                2         2          Medical             1           1504
## 626                4         2    Life Sciences             1           1259
## 630                9         3          Medical             1            717
## 632                1         3        Marketing             1           1950
## 644               16         4 Technical Degree             1           1905
## 651                1         3          Medical             1           1564
## 655                4         1 Technical Degree             1            593
## 668               10         1          Medical             1            584
## 669                7         2    Life Sciences             1           1309
## 684               24         2    Life Sciences             1            223
## 686                9         1    Life Sciences             1            581
## 689                2         3    Life Sciences             1            243
## 695                1         4          Medical             1           1700
## 703                8         2        Marketing             1           1243
## 704               20         2          Medical             1           1818
## 706               10         2    Life Sciences             1            599
## 709                6         2            Other             1           1782
## 711               17         4          Medical             1           1321
## 717               10         3        Marketing             1           1179
## 718               10         3            Other             1           1097
## 721                3         3            Other             1            689
## 722               19         3    Life Sciences             1           1631
## 724               12         5          Medical             1           1073
## 725                8         3    Life Sciences             1           1860
## 735                7         4          Medical             1           1577
## 743               13         3          Medical             1           1543
## 746               21         2 Technical Degree             1           1551
## 748                1         3          Medical             1           1184
## 749               29         1          Medical             1           1725
## 750                2         3    Life Sciences             1            242
## 751                9         3        Marketing             1           1077
## 756               24         3          Medical             1            744
## 759                4         2          Medical             1           1687
## 764                1         3    Life Sciences             1           1040
## 780                1         4          Medical             1           2027
## 783                3         2  Human Resources             1            910
## 787                3         3 Technical Degree             1           1786
## 791                3         2          Medical             1           1509
## 798                8         1          Medical             1           1783
## 835                8         1          Medical             1           1278
## 837                4         1    Life Sciences             1           1394
## 839                4         3    Life Sciences             1           1827
## 849               22         2        Marketing             1            492
## 851               20         3    Life Sciences             1            175
## 855               16         2            Other             1           1886
## 861                6         2          Medical             1           1297
## 867               26         4        Marketing             1            333
##     EnvironmentSatisfaction Gender HourlyRate JobInvolvement JobLevel
## 5                         1 Female         32              3        1
## 8                         4 Female         88              2        2
## 9                         3 Female         87              3        1
## 16                        4 Female         45              3        2
## 18                        3 Female         30              3        2
## 20                        2   Male         78              4        2
## 26                        2   Male         88              3        5
## 44                        4   Male         93              2        5
## 46                        1 Female         74              3        1
## 47                        1   Male         34              1        2
## 50                        4   Male         57              3        1
## 52                        4 Female         76              3        5
## 56                        3   Male         94              3        1
## 62                        4 Female         63              3        3
## 69                        2   Male         79              3        1
## 72                        4   Male         84              3        2
## 73                        2   Male         50              2        2
## 78                        4   Male         56              4        4
## 80                        4 Female         59              1        1
## 81                        1 Female         61              1        2
## 89                        4   Male         37              3        3
## 90                        2 Female         83              3        5
## 92                        4 Female         45              2        3
## 93                        4   Male         92              2        1
## 96                        2   Male         99              3        2
## 99                        4 Female         97              3        1
## 109                       4 Female         66              3        2
## 111                       3   Male         39              2        1
## 115                       3   Male         94              3        2
## 117                       3   Male         57              3        2
## 130                       1 Female         45              4        4
## 134                       4   Male         66              3        2
## 137                       2 Female         36              2        1
## 139                       4   Male         70              3        1
## 140                       3   Male         87              3        3
## 144                       3   Male         98              3        2
## 148                       1   Male         46              3        2
## 151                       2   Male         46              3        2
## 158                       1   Male         84              3        4
## 167                       1 Female         72              3        4
## 172                       3   Male         64              3        2
## 173                       1 Female         86              3        3
## 175                       3   Male         45              3        4
## 180                       1 Female         59              2        2
## 193                       3 Female         87              3        2
## 196                       3   Male         96              3        1
## 197                       4   Male         96              3        1
## 200                       4   Male         94              2        1
## 202                       2   Male         66              3        2
## 209                       4 Female         84              3        1
## 213                       4   Male         80              4        1
## 220                       3   Male         53              3        1
## 233                       3   Male         82              1        4
## 236                       1   Male         46              2        3
## 239                       3 Female         82              3        1
## 240                       4 Female         50              2        3
## 244                       1   Male         68              2        1
## 246                       1 Female         62              2        1
## 257                       4 Female         84              3        1
## 261                       3 Female         90              2        1
## 266                       1   Male         84              4        1
## 268                       4   Male         95              3        1
## 273                       2 Female         36              2        2
## 282                       4   Male         59              3        1
## 283                       3 Female         52              3        2
## 288                       2   Male         93              3        1
## 301                       2   Male         48              3        2
## 304                       2   Male         48              3        2
## 312                       2 Female         75              3        4
## 315                       1   Male         84              3        2
## 316                       4 Female         83              3        2
## 322                       2   Male         42              3        1
## 323                       2   Male         75              2        1
## 327                       2 Female         31              3        5
## 336                       1 Female         54              2        2
## 337                       4   Male         54              3        2
## 339                       4   Male         81              3        2
## 342                       4   Male         52              2        1
## 355                       3 Female         81              3        3
## 356                       4   Male         81              1        2
## 359                       1   Male         33              3        2
## 366                       3 Female         86              4        4
## 370                       1 Female         74              4        2
## 374                       2 Female         71              3        1
## 376                       3   Male         88              1        4
## 386                       4 Female         80              3        3
## 387                       3 Female         92              3        3
## 388                       4   Male         34              3        2
## 396                       3   Male         32              3        1
## 398                       1 Female         52              3        1
## 402                       3 Female         36              3        2
## 406                       2   Male         50              2        4
## 410                       2   Male         94              3        4
## 426                       3   Male         79              2        3
## 447                       4   Male         90              3        2
## 452                       4   Male         49              3        1
## 458                       3   Male         71              3        2
## 462                       1   Male         77              3        1
## 466                       4   Male         45              3        1
## 473                       4   Male         52              3        3
## 483                       3   Male         86              2        2
## 487                       2   Male         89              3        1
## 493                       3   Male         42              2        2
## 502                       3   Male         50              2        1
## 505                       1 Female         82              3        4
## 514                       1 Female         98              3        3
## 515                       1   Male         39              3        1
## 521                       3 Female        100              2        1
## 527                       3 Female         30              3        2
## 531                       3 Female         65              2        3
## 533                       3   Male         81              4        1
## 536                       4   Male         37              4        1
## 544                       4   Male         88              3        2
## 556                       4   Male         75              3        2
## 568                       2   Male         64              2        2
## 570                       4   Male         95              3        4
## 576                       1   Male         51              2        2
## 579                       1 Female         81              3        2
## 584                       2 Female         81              3        2
## 603                       2 Female         73              4        3
## 606                       3   Male         59              4        4
## 609                       3   Male        100              4        1
## 611                       4 Female         60              2        2
## 612                       1 Female         62              2        2
## 614                       4   Male         37              2        1
## 616                       2   Male         57              2        2
## 617                       1 Female         82              2        1
## 625                       3   Male         38              2        1
## 626                       1   Male         76              3        1
## 630                       4 Female         46              2        3
## 632                       1   Male         32              3        3
## 644                       4   Male         85              1        1
## 651                       4   Male         68              2        1
## 655                       3   Male         99              2        1
## 668                       1   Male         38              1        1
## 669                       4   Male         79              3        2
## 684                       3   Male         83              4        3
## 686                       3   Male         33              3        3
## 689                       2   Male         47              2        1
## 695                       3   Male         31              1        2
## 703                       3 Female         78              2        3
## 704                       4 Female         69              3        1
## 706                       4   Male         56              3        2
## 709                       4 Female         40              2        1
## 711                       2 Female         95              3        3
## 717                       3   Male         72              2        2
## 718                       3 Female         59              3        2
## 721                       3   Male         36              3        3
## 722                       3   Male         85              3        2
## 724                       4 Female         51              2        3
## 725                       4   Male         81              3        1
## 735                       1   Male         35              3        1
## 743                       1   Male         47              3        2
## 746                       3   Male         57              2        1
## 748                       4   Male         97              2        2
## 749                       2   Male         91              3        1
## 750                       3   Male         90              3        1
## 751                       4 Female         54              3        1
## 756                       1   Male         49              1        1
## 759                       4 Female         87              3        1
## 764                       4 Female         95              3        2
## 780                       1   Male         36              3        1
## 783                       4   Male         57              3        1
## 787                       1 Female         53              3        3
## 791                       3 Female         43              2        2
## 798                       3 Female         79              3        1
## 835                       4   Male         37              2        4
## 837                       3   Male         54              3        1
## 839                       3 Female         92              2        3
## 849                       3   Male         68              2        2
## 851                       2 Female         71              1        2
## 855                       4 Female         44              2        2
## 861                       2 Female         40              2        1
## 867                       3   Male        100              3        2
##                       JobRole JobSatisfaction MaritalStatus MonthlyIncome
## 5          Research Scientist               4        Single          3760
## 8             Sales Executive               4      Divorced          6694
## 9        Sales Representative               3       Married          2220
## 16            Sales Executive               3       Married          6932
## 18     Manufacturing Director               3       Married          5258
## 20  Healthcare Representative               1       Married          5033
## 26                    Manager               2       Married         18213
## 44                    Manager               4        Single         19613
## 46      Laboratory Technician               4        Single          3673
## 47            Sales Executive               2        Single          6735
## 50         Research Scientist               2      Divorced          2024
## 52          Research Director               1       Married         19701
## 56      Laboratory Technician               1      Divorced          2289
## 62  Healthcare Representative               3       Married          7094
## 69         Research Scientist               1       Married          2194
## 72            Sales Executive               1        Single          8463
## 73     Manufacturing Director               3       Married          5916
## 78                    Manager               1        Single         17567
## 80      Laboratory Technician               4      Divorced          1129
## 81  Healthcare Representative               2       Married          4777
## 89            Sales Executive               3        Single          8726
## 90                    Manager               1        Single         18947
## 92            Sales Executive               1       Married          7336
## 93      Laboratory Technician               3        Single          2090
## 96            Sales Executive               3       Married          4907
## 99      Laboratory Technician               2       Married          3180
## 109 Healthcare Representative               2       Married          8926
## 111        Research Scientist               3      Divorced          2703
## 115           Sales Executive               1       Married          8966
## 117           Sales Executive               4        Single          4950
## 130           Sales Executive               1      Divorced         13225
## 134    Manufacturing Director               2       Married          5295
## 137     Laboratory Technician               1       Married          2319
## 139     Laboratory Technician               1       Married          2404
## 140           Sales Executive               4        Single          7428
## 144           Sales Executive               4       Married          6502
## 148           Sales Executive               1       Married          6392
## 151           Sales Executive               1      Divorced          4233
## 158 Healthcare Representative               4      Divorced         12169
## 167         Research Director               2       Married         16413
## 172        Research Scientist               2       Married          5467
## 173 Healthcare Representative               3       Married         10527
## 175                   Manager               3      Divorced         14852
## 180           Sales Executive               4        Single          8686
## 193    Manufacturing Director               3      Divorced          4810
## 196        Research Scientist               4       Married          2723
## 197     Laboratory Technician               4       Married          2075
## 200     Laboratory Technician               2       Married          2127
## 202        Research Scientist               2       Married          6220
## 209        Research Scientist               1      Divorced          3204
## 213        Research Scientist               4        Single          4680
## 220        Research Scientist               4        Single          2875
## 233           Sales Executive               3       Married         12936
## 236           Sales Executive               3       Married         10609
## 239           Human Resources               2       Married          2187
## 240         Research Director               1      Divorced         13269
## 244      Sales Representative               1       Married          4400
## 246     Laboratory Technician               4      Divorced          2532
## 257      Sales Representative               2      Divorced          2789
## 261      Sales Representative               4        Single          2785
## 266     Laboratory Technician               2       Married          2426
## 268     Laboratory Technician               2        Single          1393
## 273      Sales Representative               3       Married          3540
## 282     Laboratory Technician               1        Single          4721
## 283 Healthcare Representative               4      Divorced          6513
## 288     Laboratory Technician               4      Divorced          2661
## 301           Sales Executive               2       Married          6524
## 304        Research Scientist               3        Single          5098
## 312    Manufacturing Director               3        Single         13237
## 315           Sales Executive               1        Single          5405
## 316           Sales Executive               4        Single          4163
## 322        Research Scientist               4       Married          2691
## 323        Research Scientist               4      Divorced          3761
## 327         Research Director               4      Divorced         19049
## 336        Research Scientist               3        Single          4508
## 337           Sales Executive               4      Divorced          4968
## 339           Sales Executive               3        Single          4728
## 342     Laboratory Technician               4       Married          3867
## 355           Sales Executive               3      Divorced         10447
## 356           Sales Executive               1        Single          4759
## 359    Manufacturing Director               4       Married          6162
## 366           Sales Executive               1       Married         13212
## 370        Research Scientist               4        Single          5055
## 374        Research Scientist               2       Married          3936
## 376         Research Director               4        Single         14411
## 386         Research Director               1       Married         13582
## 387           Sales Executive               3        Single          8789
## 388    Manufacturing Director               4      Divorced          4262
## 396        Research Scientist               4      Divorced          2695
## 398           Human Resources               3       Married          2742
## 402    Manufacturing Director               3      Divorced          5265
## 406         Research Director               4      Divorced         16627
## 410         Research Director               1       Married         17159
## 426           Sales Executive               4      Divorced         10798
## 447        Research Scientist               4       Married          4735
## 452        Research Scientist               2        Single          3420
## 458           Sales Executive               4        Single          5441
## 462     Laboratory Technician               2        Single          2013
## 466        Research Scientist               4        Single          3944
## 473         Research Director               1       Married         13245
## 483        Research Scientist               4       Married          5747
## 487      Sales Representative               4        Single          1081
## 493           Sales Executive               3        Single          5869
## 502     Laboratory Technician               3        Single          2028
## 505         Research Director               3       Married         17169
## 514         Research Director               4        Single         13458
## 515      Sales Representative               4        Single          2610
## 521        Research Scientist               4        Single          2553
## 527           Sales Executive               1      Divorced          5006
## 531 Healthcare Representative               3       Married          8823
## 533        Research Scientist               3       Married          2700
## 536        Research Scientist               4      Divorced          2089
## 544    Manufacturing Director               3       Married          6553
## 556           Sales Executive               3       Married          9602
## 568           Sales Executive               1       Married          9714
## 570    Manufacturing Director               3       Married         13973
## 576    Manufacturing Director               3      Divorced          5993
## 579    Manufacturing Director               3        Single          5042
## 584           Sales Executive               2       Married          4779
## 603         Research Director               1       Married         11416
## 606         Research Director               3       Married         14814
## 609     Laboratory Technician               1        Single          3578
## 611     Laboratory Technician               4       Married          5363
## 612 Healthcare Representative               3        Single          6811
## 614      Sales Representative               2        Single          2121
## 616     Laboratory Technician               4       Married          3986
## 617     Laboratory Technician               2       Married          3838
## 625     Laboratory Technician               1        Single          2561
## 626        Research Scientist               3      Divorced          2517
## 630 Healthcare Representative               2        Single          8621
## 632           Sales Executive               4        Single          9888
## 644        Research Scientist               1       Married          2307
## 651     Laboratory Technician               1        Single          2450
## 655     Laboratory Technician               3        Single          3894
## 668     Laboratory Technician               4      Divorced          3408
## 669     Laboratory Technician               3       Married          4883
## 684 Healthcare Representative               4      Divorced          9439
## 686    Manufacturing Director               2      Divorced         10648
## 689     Laboratory Technician               4        Single          1102
## 695           Sales Executive               4      Divorced          9525
## 703           Sales Executive               4       Married         10377
## 704           Human Resources               2       Married          2148
## 706           Sales Executive               4        Single          6230
## 709     Laboratory Technician               3       Married          3702
## 711                   Manager               1       Married         11916
## 717           Sales Executive               3       Married          6578
## 718        Research Scientist               3        Single          3660
## 721    Manufacturing Director               3       Married          9434
## 722    Manufacturing Director               3       Married          5768
## 724    Manufacturing Director               4        Single          8858
## 725     Laboratory Technician               3        Single          3968
## 735        Research Scientist               4        Single          2972
## 743        Research Scientist               4       Married          4285
## 746     Laboratory Technician               1      Divorced          2296
## 748 Healthcare Representative               1        Single          5343
## 749     Laboratory Technician               1      Divorced          3907
## 750        Research Scientist               4        Single          2500
## 751      Sales Representative               4        Single          2323
## 756     Laboratory Technician               3        Single          3708
## 759     Laboratory Technician               3       Married          3306
## 764           Sales Executive               3       Married          6347
## 780        Research Scientist               4       Married          4787
## 783           Human Resources               2      Divorced          2277
## 787                   Manager               3       Married         13116
## 791     Laboratory Technician               1       Married          4789
## 798     Laboratory Technician               1       Married          2398
## 835 Healthcare Representative               2      Divorced         13577
## 837        Research Scientist               3       Married          2996
## 839    Manufacturing Director               2      Divorced         10333
## 849           Sales Executive               3       Married          6380
## 851           Sales Executive               3       Married          4559
## 855    Manufacturing Director               2       Married          4788
## 861     Laboratory Technician               3        Single          2838
## 867           Sales Executive               4       Married          4465
##     MonthlyRate NumCompaniesWorked OverTime PercentSalaryHike PerformanceRating
## 5         17218                  1      Yes                13                 3
## 8         24223                  2      Yes                14                 3
## 9         18410                  1      Yes                19                 3
## 16        24406                  1       No                13                 3
## 18        16044                  2       No                14                 3
## 20         9364                  2       No                15                 3
## 26         8751                  7       No                11                 3
## 44        26362                  8       No                22                 4
## 46        16458                  1       No                13                 3
## 47        12147                  6       No                15                 3
## 50         5970                  6       No                18                 3
## 52        22456                  3      Yes                21                 4
## 56        20520                  1       No                20                 4
## 62         5747                  3       No                12                 3
## 69         5868                  4       No                13                 3
## 72        23490                  0       No                18                 3
## 73        15497                  3      Yes                13                 3
## 78         3156                  1       No                15                 3
## 80        17536                  1      Yes                11                 3
## 81        14382                  5       No                15                 3
## 89         2975                  1       No                15                 3
## 90        22822                  3       No                12                 3
## 92        11162                  1       No                13                 3
## 93         2396                  6      Yes                15                 3
## 96        24532                  1       No                25                 4
## 99         4668                  0       No                13                 3
## 109       10842                  4       No                22                 4
## 111       22088                  1      Yes                14                 3
## 115       21026                  3      Yes                15                 3
## 117       20623                  0       No                14                 3
## 130        7739                  2       No                12                 3
## 134        7693                  4       No                21                 4
## 137        6689                  1      Yes                11                 3
## 139        4303                  7      Yes                21                 4
## 140       14506                  2       No                12                 3
## 144       22825                  4       No                14                 3
## 148       10589                  2       No                13                 3
## 151       11512                  2       No                17                 3
## 158       13547                  7       No                11                 3
## 167        3498                  3       No                16                 3
## 172        2125                  8       No                18                 3
## 173        8984                  5       No                11                 3
## 175       13938                  6       No                13                 3
## 180       12930                  4       No                22                 4
## 193       26314                  2       No                14                 3
## 196       23231                  1       No                11                 3
## 197       18725                  3       No                23                 4
## 200        9100                  1       No                21                 4
## 202        7346                  1       No                17                 3
## 209       10415                  5       No                14                 3
## 213       15232                  3       No                17                 3
## 220        9973                  1      Yes                20                 4
## 233       24164                  7       No                11                 3
## 236       14922                  5       No                11                 3
## 239       19655                  4       No                14                 3
## 240       21981                  5       No                15                 3
## 244       15182                  3       No                12                 3
## 246        6054                  6       No                14                 3
## 257        3909                  1       No                11                 3
## 261       11882                  7       No                14                 3
## 266       16479                  0       No                13                 3
## 268       24852                  1       No                12                 3
## 273        7018                  1       No                21                 4
## 282        3119                  2      Yes                13                 3
## 283        9060                  4       No                17                 3
## 288        8758                  0       No                11                 3
## 301        8891                  1       No                14                 3
## 304       18698                  1       No                19                 3
## 312       20364                  7       No                15                 3
## 315       11924                  8       No                14                 3
## 316        8571                  1      Yes                17                 3
## 322        7660                  1       No                12                 3
## 323        2373                  9       No                12                 3
## 327        3549                  0      Yes                14                 3
## 336        3129                  1       No                22                 4
## 337       18500                  1       No                11                 3
## 339       17251                  3      Yes                14                 3
## 342       14222                  1      Yes                12                 3
## 355       26458                  0      Yes                13                 3
## 356       15891                  3       No                18                 3
## 359       10877                  1      Yes                22                 4
## 366       18256                  9       No                11                 3
## 370       10557                  7       No                16                 3
## 374        9953                  1       No                11                 3
## 376       24450                  1      Yes                13                 3
## 386       16292                  1       No                13                 3
## 387        9096                  1       No                14                 3
## 388       22645                  4       No                12                 3
## 396        7747                  0      Yes                18                 3
## 398        3072                  1       No                15                 3
## 402       16439                  2       No                16                 3
## 406        2671                  4      Yes                14                 3
## 410        5200                  6       No                24                 4
## 426        5268                  5       No                13                 3
## 447        9867                  7       No                15                 3
## 452       21158                  1       No                13                 3
## 458        8423                  0      Yes                22                 4
## 462       10950                  2       No                11                 3
## 466        4306                  5      Yes                11                 3
## 473       15067                  4      Yes                14                 3
## 483       26496                  1      Yes                15                 3
## 487       16019                  1       No                13                 3
## 493       23413                  9       No                11                 3
## 502       12947                  5      Yes                14                 3
## 505       26703                  3       No                19                 3
## 514       15146                  1      Yes                12                 3
## 515        2851                  1       No                24                 4
## 521        8306                  1       No                16                 3
## 527        6319                  4      Yes                11                 3
## 531       24608                  0       No                18                 3
## 533       23779                  1       No                24                 4
## 536        5228                  4       No                14                 3
## 544        7259                  9       No                14                 3
## 556        3010                  4      Yes                11                 3
## 568        5323                  1       No                11                 3
## 570        4161                  3      Yes                18                 3
## 576        2689                  1       No                18                 3
## 579        3140                  0       No                13                 3
## 584        3698                  1      Yes                20                 4
## 603       17802                  0      Yes                12                 3
## 606       13514                  3       No                19                 3
## 609       23577                  0       No                12                 3
## 611       10846                  0       No                12                 3
## 612        2112                  2      Yes                17                 3
## 614        9947                  1      Yes                13                 3
## 616       11912                  1       No                14                 3
## 617        8192                  8       No                11                 3
## 625        5355                  7       No                11                 3
## 626        3208                  1       No                11                 3
## 630       17654                  1       No                14                 3
## 632        6770                  1       No                21                 4
## 644       14460                  1      Yes                23                 4
## 651       21731                  1       No                19                 3
## 655        9129                  5       No                16                 3
## 668        6705                  7       No                13                 3
## 669       22845                  1       No                18                 3
## 684       23402                  3      Yes                16                 3
## 686       14394                  1       No                25                 4
## 689        9241                  1       No                22                 4
## 695        7677                  1       No                14                 3
## 703       13755                  4      Yes                11                 3
## 704        6889                  0      Yes                11                 3
## 706       13430                  7       No                14                 3
## 709       16376                  1       No                11                 3
## 711       25927                  1      Yes                23                 4
## 717        2706                  1       No                18                 3
## 718        7909                  3       No                13                 3
## 721        9606                  1       No                15                 3
## 722       26493                  3       No                17                 3
## 724       15669                  0       No                11                 3
## 725       13624                  4       No                13                 3
## 735       22061                  1       No                13                 3
## 743        3031                  1       No                17                 3
## 746       10036                  0       No                14                 3
## 748       25755                  0       No                20                 4
## 749        3622                  1       No                13                 3
## 750       10515                  0       No                14                 3
## 751       17205                  1      Yes                14                 3
## 756        2104                  2       No                14                 3
## 759       26176                  7       No                19                 3
## 764       24920                  0       No                12                 3
## 780       26124                  9      Yes                14                 3
## 783       22650                  3      Yes                11                 3
## 787       22984                  2       No                11                 3
## 791       23070                  4       No                25                 4
## 798       15999                  1      Yes                17                 3
## 835       25592                  1      Yes                15                 3
## 837        5182                  7      Yes                15                 3
## 839       19271                  8      Yes                12                 3
## 849        6110                  2      Yes                12                 3
## 851       24788                  3      Yes                11                 3
## 855       25388                  0      Yes                11                 3
## 861        4257                  0       No                14                 3
## 867       12069                  0       No                18                 3
##     RelationshipSatisfaction StandardHours StockOptionLevel TotalWorkingYears
## 5                          3            80                0                 6
## 8                          3            80                3                 8
## 9                          4            80                1                 1
## 16                         4            80                1                 9
## 18                         3            80                0                 7
## 20                         4            80                1                10
## 26                         3            80                1                26
## 44                         4            80                0                24
## 46                         3            80                0                12
## 47                         2            80                0                10
## 50                         4            80                1                 6
## 52                         3            80                1                32
## 56                         2            80                2                 5
## 62                         1            80                0                10
## 69                         4            80                1                 5
## 72                         4            80                0                 6
## 73                         1            80                0                 8
## 78                         2            80                0                27
## 80                         3            80                3                 1
## 81                         1            80                0                15
## 89                         4            80                0                 9
## 90                         4            80                0                22
## 92                         1            80                1                11
## 93                         2            80                0                 7
## 96                         3            80                0                20
## 99                         3            80                3                 4
## 109                        4            80                1                13
## 111                        4            80                1                 3
## 115                        4            80                3                15
## 117                        2            80                0                 5
## 130                        4            80                1                25
## 134                        3            80                0                 7
## 137                        4            80                1                 1
## 139                        4            80                0                 8
## 140                        1            80                0                12
## 144                        2            80                1                 7
## 148                        4            80                1                 8
## 151                        3            80                0                 9
## 158                        4            80                3                21
## 167                        2            80                2                27
## 172                        3            80                1                16
## 173                        4            80                0                28
## 175                        3            80                1                22
## 180                        3            80                0                12
## 193                        3            80                1                19
## 196                        2            80                0                 1
## 197                        2            80                2                10
## 200                        4            80                1                 1
## 202                        2            80                2                10
## 209                        4            80                1                 8
## 213                        1            80                0                 4
## 220                        2            80                0                 8
## 233                        3            80                0                25
## 236                        3            80                0                17
## 239                        3            80                0                 6
## 240                        3            80                3                19
## 244                        1            80                0                 6
## 246                        3            80                3                 8
## 257                        3            80                1                 2
## 261                        3            80                0                 3
## 266                        3            80                1                 6
## 268                        1            80                0                 1
## 273                        4            80                1                 9
## 282                        3            80                0                20
## 283                        4            80                1                12
## 288                        3            80                1                 3
## 301                        4            80                1                10
## 304                        2            80                0                10
## 312                        3            80                0                22
## 315                        4            80                0                10
## 316                        3            80                0                 9
## 322                        4            80                1                10
## 323                        2            80                1                10
## 327                        4            80                1                23
## 336                        2            80                0                14
## 337                        4            80                1                 5
## 339                        4            80                0                 5
## 342                        2            80                1                 2
## 355                        4            80                1                23
## 356                        4            80                0                15
## 359                        2            80                1                 9
## 366                        4            80                3                36
## 370                        3            80                0                10
## 374                        1            80                1                 8
## 376                        4            80                0                32
## 386                        2            80                1                15
## 387                        1            80                0                10
## 388                        2            80                2                 8
## 396                        2            80                1                 3
## 398                        4            80                0                 2
## 402                        2            80                1                11
## 406                        3            80                1                21
## 410                        3            80                1                22
## 426                        3            80                1                18
## 447                        4            80                2                19
## 452                        3            80                0                 6
## 458                        4            80                0                11
## 462                        3            80                0                15
## 466                        3            80                0                 6
## 473                        2            80                0                17
## 483                        2            80                0                16
## 487                        3            80                0                 1
## 493                        3            80                0                 8
## 502                        2            80                0                 6
## 505                        2            80                2                26
## 514                        3            80                0                15
## 515                        3            80                0                 3
## 521                        3            80                0                 6
## 527                        1            80                1                 9
## 531                        1            80                1                20
## 533                        3            80                1                10
## 536                        4            80                3                 7
## 544                        2            80                0                14
## 556                        3            80                1                17
## 568                        4            80                1                10
## 570                        4            80                1                22
## 576                        3            80                1                 7
## 579                        4            80                0                10
## 584                        1            80                0                 8
## 603                        3            80                3                 9
## 606                        3            80                0                32
## 609                        4            80                0                 8
## 611                        2            80                1                10
## 612                        1            80                0                10
## 614                        2            80                0                 1
## 616                        3            80                1                15
## 617                        4            80                0                 8
## 625                        3            80                0                 8
## 626                        2            80                3                 5
## 630                        2            80                0                 9
## 632                        1            80                0                14
## 644                        2            80                1                 5
## 651                        2            80                0                 3
## 655                        3            80                0                 4
## 668                        1            80                3                 8
## 669                        1            80                1                10
## 684                        2            80                1                12
## 686                        4            80                1                13
## 689                        3            80                0                 1
## 695                        3            80                2                 6
## 703                        2            80                1                16
## 704                        3            80                0                 6
## 706                        4            80                0                16
## 709                        2            80                1                 5
## 711                        4            80                2                 9
## 717                        1            80                1                10
## 718                        4            80                0                10
## 721                        3            80                1                10
## 722                        1            80                3                 9
## 724                        2            80                0                15
## 725                        4            80                0                 8
## 735                        3            80                0                 1
## 743                        1            80                0                10
## 746                        2            80                3                 2
## 748                        3            80                0                14
## 749                        2            80                3                 6
## 750                        1            80                0                 4
## 751                        2            80                0                 2
## 756                        3            80                0                 9
## 759                        4            80                1                 7
## 764                        1            80                1                19
## 780                        2            80                3                 4
## 783                        3            80                1                 7
## 787                        4            80                0                15
## 791                        1            80                1                10
## 798                        3            80                0                 1
## 835                        4            80                1                34
## 837                        4            80                0                 8
## 839                        3            80                1                28
## 849                        1            80                2                 8
## 851                        3            80                1                 4
## 855                        4            80                0                 4
## 861                        2            80                0                 8
## 867                        1            80                0                 4
##     TrainingTimesLastYear WorkLifeBalance YearsAtCompany YearsInCurrentRole
## 5                       2               3              6                  3
## 8                       5               3              1                  0
## 9                       2               3              1                  1
## 16                      2               2              9                  8
## 18                      2               4              1                  0
## 20                      5               3              2                  0
## 26                      5               3             22                  9
## 44                      2               3              1                  0
## 46                      3               3             12                  9
## 47                      2               3              0                  0
## 50                      1               1              2                  2
## 52                      3               3              9                  8
## 56                      2               3              5                  3
## 62                      0               3              7                  7
## 69                      2               2              3                  2
## 72                      4               3              5                  4
## 73                      1               3              1                  0
## 78                      5               1             26                  0
## 80                      4               3              1                  0
## 81                      2               1              1                  0
## 89                      0               3              9                  8
## 90                      2               2              2                  2
## 92                      3               1             11                  8
## 93                      3               3              0                  0
## 96                      3               3             20                 16
## 99                      3               3              3                  2
## 109                     2               4              9                  7
## 111                     2               3              3                  1
## 115                     2               3              7                  7
## 117                     4               3              4                  3
## 130                     5               3             19                 17
## 134                     3               3              5                  4
## 137                     1               3              1                  0
## 139                     2               1              2                  2
## 140                     3               3              5                  3
## 144                     5               4              5                  4
## 148                     6               1              2                  2
## 151                     2               1              3                  1
## 158                     4               3             18                  7
## 167                     2               3              4                  2
## 172                     4               4              8                  7
## 173                     3               2              2                  2
## 175                     3               4             17                 13
## 180                     2               4              8                  3
## 193                     5               2             10                  7
## 196                     0               2              1                  0
## 197                     4               3              4                  2
## 200                     2               3              1                  0
## 202                     3               3             10                  4
## 209                     3               3              3                  2
## 213                     2               3              1                  0
## 220                     2               2              8                  5
## 233                     3               1             23                  5
## 236                     2               1             14                  1
## 239                     3               3              2                  0
## 240                     3               3             14                 11
## 244                     2               3              3                  2
## 246                     5               3              4                  3
## 257                     5               2              2                  2
## 261                     3               4              1                  0
## 266                     5               3              5                  4
## 268                     2               3              1                  0
## 273                     5               3              9                  8
## 282                     3               3             18                 13
## 283                     3               3              5                  3
## 288                     2               3              2                  2
## 301                     3               3             10                  8
## 304                     5               3             10                  7
## 312                     3               3             20                  6
## 315                     1               3              2                  2
## 316                     0               3              9                  0
## 322                     4               2             10                  9
## 323                     3               2              5                  4
## 327                     4               2             22                  7
## 336                     4               3             13                  7
## 337                     3               3              5                  2
## 339                     4               3              0                  0
## 342                     2               3              2                  2
## 355                     3               4             22                 14
## 356                     2               3             13                  9
## 359                     3               3              9                  8
## 366                     0               2              7                  7
## 370                     0               2              7                  7
## 374                     2               1              8                  4
## 376                     2               3             32                  6
## 386                     3               3             15                 12
## 387                     3               4             10                  7
## 388                     2               4              3                  2
## 396                     2               1              2                  2
## 398                     0               3              2                  2
## 402                     5               3              5                  3
## 406                     3               2              1                  0
## 410                     3               3              4                  1
## 426                     5               3              1                  0
## 447                     4               4             13                 11
## 452                     3               2              5                  2
## 458                     2               1             10                  7
## 462                     4               3              4                  3
## 466                     3               3              3                  2
## 473                     3               4              0                  0
## 483                     3               3             15                 10
## 487                     3               2              1                  0
## 493                     2               3              5                  2
## 502                     4               3              4                  2
## 505                     2               4             20                 17
## 514                     1               3             15                 14
## 515                     3               2              3                  2
## 521                     3               3              5                  2
## 527                     3               4              5                  4
## 531                     4               2             19                  9
## 533                     3               3             10                  7
## 536                     3               4              5                  4
## 544                     3               3              1                  0
## 556                     3               2              3                  0
## 568                     4               3             10                  8
## 570                     2               3             12                 11
## 576                     2               4              7                  5
## 579                     2               1              9                  2
## 584                     2               3              8                  7
## 603                     4               2              8                  7
## 606                     3               3              5                  1
## 609                     2               3              7                  7
## 611                     0               3              9                  7
## 612                     3               3              8                  7
## 614                     3               4              1                  0
## 616                     3               4             15                 10
## 617                     5               3              5                  4
## 625                     2               2              0                  0
## 626                     2               3              5                  3
## 630                     3               4              8                  7
## 632                     3               2             14                  8
## 644                     2               3              5                  2
## 651                     3               3              3                  0
## 655                     3               3              2                  2
## 668                     2               3              4                  3
## 669                     3               3             10                  4
## 684                     2               1              5                  3
## 686                     6               4             13                  8
## 689                     3               2              1                  0
## 695                     2               2              6                  3
## 703                     6               2             13                  2
## 704                     3               3              5                  1
## 706                     3               3             14                  3
## 709                     3               3              5                  4
## 711                     2               3              9                  1
## 717                     3               3             10                  3
## 718                     4               4              8                  7
## 721                     2               3             10                  7
## 722                     2               2              4                  3
## 724                     2               2             14                  8
## 725                     3               3              0                  0
## 735                     4               1              1                  0
## 743                     2               3             10                  8
## 746                     3               3              1                  1
## 748                     3               3             13                  9
## 749                     2               4              6                  2
## 750                     2               4              3                  1
## 751                     3               3              2                  2
## 756                     5               3              5                  2
## 759                     5               2              0                  0
## 764                     3               3             18                  7
## 780                     3               4              2                  2
## 783                     4               4              4                  3
## 787                     2               3              2                  2
## 791                     3               3              3                  2
## 798                     6               3              1                  0
## 835                     3               3             33                  9
## 837                     2               3              6                  4
## 839                     4               3             22                 11
## 849                     6               3              6                  4
## 851                     2               3              2                  2
## 855                     2               3              3                  2
## 861                     6               2              7                  0
## 867                     2               3              3                  2
##     YearsSinceLastPromotion YearsWithCurrManager
## 5                         1                    3
## 8                         0                    0
## 9                         0                    0
## 16                        0                    0
## 18                        0                    0
## 20                        2                    2
## 26                        3                   10
## 44                        0                    1
## 46                        5                    8
## 47                        0                    0
## 50                        2                    2
## 52                        1                    5
## 56                        0                    4
## 62                        1                    7
## 69                        1                    2
## 72                        1                    3
## 73                        0                    1
## 78                        0                   12
## 80                        0                    0
## 81                        0                    0
## 89                        1                    7
## 90                        2                    1
## 92                        3                   10
## 93                        0                    0
## 96                       11                    6
## 99                        0                    2
## 109                       3                    7
## 111                       0                    2
## 115                       1                    7
## 117                       1                    1
## 130                       2                    8
## 134                       1                    0
## 137                       0                    0
## 139                       2                    2
## 140                       1                    3
## 144                       0                    1
## 148                       2                    2
## 151                       1                    2
## 158                      11                    5
## 167                       1                    2
## 172                       1                    7
## 173                       1                    2
## 175                      15                    2
## 180                       0                    7
## 193                       0                    8
## 196                       0                    0
## 197                       0                    3
## 200                       0                    0
## 202                       0                    9
## 209                       2                    2
## 213                       0                    0
## 220                       2                    2
## 233                      14                   10
## 236                      11                    7
## 239                       1                    2
## 240                       1                   11
## 244                       2                    2
## 246                       0                    3
## 257                       2                    2
## 261                       0                    0
## 266                       0                    3
## 268                       0                    0
## 273                       5                    8
## 282                       2                   17
## 283                       0                    3
## 288                       1                    2
## 301                       5                    3
## 304                       0                    8
## 312                       5                   13
## 315                       2                    2
## 316                       0                    7
## 322                       8                    8
## 323                       0                    3
## 327                       1                   10
## 336                       3                    8
## 337                       0                    2
## 339                       0                    0
## 342                       2                    2
## 355                      13                    5
## 356                       3                   12
## 359                       7                    8
## 366                       7                    7
## 370                       0                    7
## 374                       7                    7
## 376                      13                    9
## 386                       5                   11
## 387                       0                    8
## 388                       1                    2
## 396                       2                    2
## 398                       2                    2
## 402                       0                    2
## 406                       0                    0
## 410                       1                    0
## 426                       0                    0
## 447                       2                    9
## 452                       1                    3
## 458                       1                    0
## 462                       1                    3
## 466                       1                    2
## 473                       0                    0
## 483                       6                   11
## 487                       0                    0
## 493                       1                    4
## 502                       0                    3
## 505                       5                    6
## 514                       8                   12
## 515                       2                    2
## 521                       1                    3
## 527                       0                    3
## 531                       1                    9
## 533                       0                    7
## 536                       2                    2
## 544                       0                    0
## 556                       1                    0
## 568                       6                    7
## 570                       1                    5
## 576                       0                    7
## 579                       3                    8
## 584                       7                    5
## 603                       1                    7
## 606                       1                    3
## 609                       0                    7
## 611                       0                    0
## 612                       0                    7
## 614                       0                    0
## 616                       4                   13
## 617                       0                    2
## 625                       0                    0
## 626                       0                    3
## 630                       7                    7
## 632                       2                    1
## 644                       3                    0
## 651                       1                    2
## 655                       1                    2
## 668                       1                    3
## 669                       1                    1
## 684                       1                    4
## 686                       0                    8
## 689                       1                    0
## 695                       1                    3
## 703                       4                   12
## 704                       1                    4
## 706                       1                   10
## 709                       0                    4
## 711                       0                    8
## 717                       1                    4
## 718                       1                    7
## 721                       7                    8
## 722                       0                    2
## 724                       7                    8
## 725                       0                    0
## 735                       0                    0
## 743                       3                    7
## 746                       0                    0
## 748                       4                    9
## 749                       1                    2
## 750                       0                    2
## 751                       0                    2
## 756                       1                    4
## 759                       0                    0
## 764                       0                   13
## 780                       2                    2
## 783                       0                    3
## 787                       2                    2
## 791                       1                    2
## 798                       0                    0
## 835                      15                    0
## 837                       1                    3
## 839                      14                   10
## 849                       1                    0
## 851                       2                    2
## 855                       0                    2
## 861                       7                    7
## 867                       2                    2
Model1_fit <- lm(MonthlyIncome ~ ., data = Attritiondata)
summary(Model1_fit)
## 
## Call:
## lm(formula = MonthlyIncome ~ ., data = Attritiondata)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -3708.8  -674.1    14.7   614.1  4100.0 
## 
## Coefficients: (2 not defined because of singularities)
##                                    Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                       6.013e+01  7.772e+02   0.077 0.938349    
## ID                               -2.343e-01  1.476e-01  -1.588 0.112713    
## Age                              -1.431e+00  5.649e+00  -0.253 0.800110    
## AttritionYes                      8.904e+01  1.154e+02   0.771 0.440729    
## BusinessTravelTravel_Frequently   1.895e+02  1.420e+02   1.334 0.182441    
## BusinessTravelTravel_Rarely       3.720e+02  1.200e+02   3.099 0.002005 ** 
## DailyRate                         1.452e-01  9.129e-02   1.591 0.112062    
## DepartmentResearch & Development  1.234e+02  4.768e+02   0.259 0.795866    
## DepartmentSales                  -4.594e+02  4.877e+02  -0.942 0.346580    
## DistanceFromHome                 -6.237e+00  4.578e+00  -1.362 0.173417    
## Education                        -3.743e+01  3.716e+01  -1.007 0.314105    
## EducationFieldLife Sciences       1.352e+02  3.692e+02   0.366 0.714248    
## EducationFieldMarketing           1.377e+02  3.914e+02   0.352 0.725050    
## EducationFieldMedical             3.326e+01  3.699e+02   0.090 0.928376    
## EducationFieldOther               9.152e+01  3.946e+02   0.232 0.816664    
## EducationFieldTechnical Degree    9.680e+01  3.843e+02   0.252 0.801179    
## EmployeeCount                            NA         NA      NA       NA    
## EmployeeNumber                    8.681e-02  6.103e-02   1.422 0.155269    
## EnvironmentSatisfaction          -6.267e+00  3.364e+01  -0.186 0.852252    
## GenderMale                        1.100e+02  7.442e+01   1.478 0.139715    
## HourlyRate                       -3.591e-01  1.824e+00  -0.197 0.844003    
## JobInvolvement                    1.677e+01  5.321e+01   0.315 0.752698    
## JobLevel                          2.783e+03  8.340e+01  33.375  < 2e-16 ***
## JobRoleHuman Resources           -2.053e+02  5.157e+02  -0.398 0.690663    
## JobRoleLaboratory Technician     -5.891e+02  1.714e+02  -3.437 0.000618 ***
## JobRoleManager                    4.280e+03  2.830e+02  15.122  < 2e-16 ***
## JobRoleManufacturing Director     1.809e+02  1.696e+02   1.067 0.286497    
## JobRoleResearch Director          4.077e+03  2.193e+02  18.592  < 2e-16 ***
## JobRoleResearch Scientist        -3.494e+02  1.705e+02  -2.049 0.040790 *  
## JobRoleSales Executive            5.263e+02  3.576e+02   1.472 0.141449    
## JobRoleSales Representative       8.531e+01  3.918e+02   0.218 0.827703    
## JobSatisfaction                   3.278e+01  3.344e+01   0.980 0.327278    
## MaritalStatusMarried              6.708e+01  1.002e+02   0.669 0.503497    
## MaritalStatusSingle               1.128e+01  1.361e+02   0.083 0.933978    
## MonthlyRate                      -9.505e-03  5.143e-03  -1.848 0.064946 .  
## NumCompaniesWorked                5.421e+00  1.691e+01   0.321 0.748622    
## OverTimeYes                      -1.394e+01  8.434e+01  -0.165 0.868787    
## PercentSalaryHike                 2.586e+01  1.581e+01   1.635 0.102351    
## PerformanceRating                -3.235e+02  1.614e+02  -2.004 0.045368 *  
## RelationshipSatisfaction          1.640e+01  3.339e+01   0.491 0.623375    
## StandardHours                            NA         NA      NA       NA    
## StockOptionLevel                 -2.758e+00  5.740e+01  -0.048 0.961695    
## TotalWorkingYears                 5.080e+01  1.098e+01   4.627  4.3e-06 ***
## TrainingTimesLastYear             2.436e+01  2.912e+01   0.837 0.403111    
## WorkLifeBalance                  -3.472e+01  5.161e+01  -0.673 0.501284    
## YearsAtCompany                   -2.750e+00  1.370e+01  -0.201 0.840925    
## YearsInCurrentRole                3.398e+00  1.711e+01   0.199 0.842584    
## YearsSinceLastPromotion           3.084e+01  1.532e+01   2.013 0.044405 *  
## YearsWithCurrManager             -2.691e+01  1.669e+01  -1.613 0.107210    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1055 on 823 degrees of freedom
## Multiple R-squared:  0.9501, Adjusted R-squared:  0.9473 
## F-statistic: 340.7 on 46 and 823 DF,  p-value: < 2.2e-16
#Model1_Preds = predict(Model1_fit, newdata = NoSalary)
#as.data.frame(Model1_Preds)
#write.csv(Model1_Preds,"Model1PredictionsNoSalaryRenuKarthikeyan")
    
#Cross Validation and Mean Square Predictor Error Calculation
    numMSPEs = 1000
    MSPEHolderModel1 = numeric(numMSPEs)
    MSPEHolderModel2 = numeric(numMSPEs)
    RMSEHolderModel1 = numeric(numMSPEs)
    RMSEHolderModel2 = numeric(numMSPEs)
    
    for (i in 1:numMSPEs)
    {
      TrainObs = sample(seq(1,dim(Attritiondata)[1]),round(.8*dim(Attritiondata)[1]),replace = FALSE)
      SalaryTrain = Attritiondata[TrainObs,]
      SalaryTrain
      SalaryTest = Attritiondata[-TrainObs,]
      SalaryTest
      Model1_fit <- lm(MonthlyIncome ~ ., data = SalaryTrain)
      Model1_Preds = predict(Model1_fit, newdata = SalaryTest)
      
      #MSPE Model 1
      MSPE = mean((SalaryTest$MonthlyIncome - Model1_Preds)^2)
      MSPE
      MSPEHolderModel1[i] = MSPE
      RMSEHolderModel1[i] = sqrt(MSPE)
      
      
      #Model 2
      Model2_fit = lm(MonthlyIncome ~ NumCompaniesWorked + Age + Gender + MaritalStatus + JobInvolvement + JobRole + DistanceFromHome + JobLevel + Education, data = SalaryTrain)
      Model2_Preds = predict(Model2_fit,newdata = SalaryTest)
      MSPE = mean((SalaryTest$MonthlyIncome - Model2_Preds)^2)
      MSPE
      MSPEHolderModel2[i] = MSPE
      RMSEHolderModel2[i] = sqrt(MSPE)
    }
    
    mean(MSPEHolderModel1)
## [1] 1196649
    mean(MSPEHolderModel2)
## [1] 1194877
    mean(RMSEHolderModel1)
## [1] 1091.936
    mean(RMSEHolderModel2)
## [1] 1091.156
  • Data was split 80/20 – for training and testing
  • Ran both model 1 and 2 to predict Monthly Income on the testing set
  • Cross Validation Process with 1000 iterations where MSPE and RMSE are calculated for both models
  • Summary Statistics of mean MSPE and mean RMSE for both models

Conclusion: Model 2 is the better fit as it has a lower mean RMSE and lower mean MSPE

KNN and Naive Bayes

When I initially attempted to use all predictors for KNN, each time, the model would unfortunately run into errors and say “Warning: NAs introduced by coercionError in knn(train_predictors, test_predictors, response_train, prob = TRUE,: NA/NaN/Inf in foreign function call (arg 6)”, although there are no missing values in the Attritiondata data set. I later realized that it was due to NAs being assigned to the categorical variables during the KNN chunk. I created dummy columns for these categorical variables to get the KNN to function without running into errors. Below is the code used to create the dummy columns from the FastDummies package in R.

Preparation of the Data - Including Dummy Columns for Categorical Variables

Attritiondata$BusinessTravel<- as.factor(Attritiondata$BusinessTravel)
Attritiondata$Department<- as.factor(Attritiondata$Department)
Attritiondata$EducationField<- as.factor(Attritiondata$EducationField)
Attritiondata$Gender<- as.factor(Attritiondata$Gender)
Attritiondata$JobRole<- as.factor(Attritiondata$JobRole)
Attritiondata$MaritalStatus<- as.factor(Attritiondata$MaritalStatus)
Attritiondata$OverTime<- as.factor(Attritiondata$OverTime)


Attritiondata<-dummy_cols(Attritiondata,select_columns=c("BusinessTravel","MaritalStatus","JobRole","Department","EducationField","OverTime","Gender"))

Attritiondata <- Attritiondata %>% select(-c("BusinessTravel","MaritalStatus","JobRole","Department","EducationField","OverTime","Gender"))

#Doing Same for Attrition Test Data Set (AttritionTest)
AttritionTest$BusinessTravel<- as.factor(AttritionTest$BusinessTravel)
AttritionTest$Department<- as.factor(AttritionTest$Department)
AttritionTest$EducationField<- as.factor(AttritionTest$EducationField)
AttritionTest$Gender<- as.factor(AttritionTest$Gender)
AttritionTest$JobRole<- as.factor(AttritionTest$JobRole)
AttritionTest$MaritalStatus<- as.factor(AttritionTest$MaritalStatus)
AttritionTest$OverTime<- as.factor(AttritionTest$OverTime)


AttritionTest<-dummy_cols(AttritionTest,select_columns=c("BusinessTravel","MaritalStatus","JobRole","Department","EducationField","OverTime","Gender"))

AttritionTest <- AttritionTest %>% select(-c("BusinessTravel","MaritalStatus","JobRole","Department","EducationField","OverTime","Gender"))


diff_columns_df1 <- setdiff(names(Attritiondata), names(AttritionTest))
cat("Columns in df2 but not in df1:", paste(diff_columns_df1, collapse = ", "), "\n")
## Columns in df2 but not in df1: Attrition

KNN Model and Confusion Matrix - Training with All predictors

set.seed(1234)
iterations <- 100
numks <- 10
splitPerc <- 0.8

masterAcc <- matrix(nrow = iterations, ncol = numks)


for (j in 1:iterations) {
  trainIndices <- sample(1:dim(Attritiondata)[1], round(splitPerc * dim(Attritiondata)[1]))
  train <- as.data.frame(Attritiondata[trainIndices, ])
  test <- as.data.frame(Attritiondata[-trainIndices, ])
  
  response_variable <- "Attrition"
  response_train <- factor(train[[response_variable]])
  response_test <- factor(test[[response_variable]])
 
  
  # Select columns for predictors
  selected_columns <- c(1, 2, 4:36)  # Adjust this range as needed
  
  #selected_columns <- c("ID","Age","BusinessTravel","DailyRate","Department", "DistanceFromHome", "Education", "EducationField", "EmployeeCount", "EmployeeNumber","EnvironmentSatisfaction", "Gender", "HourlyRate", "JobInvolvement", "JobLevel", "JobRole", "JobSatisfaction", "MaritalStatus", "MonthlyIncome", "MonthlyRate", "NumCompaniesWorked", "OverTime", "PercentSalaryHike", "PerformanceRating", "RelationshipSatisfaction", "StandardHours", "StockOptionLevel", "TotalWorkingYears", "TrainingTimesLastYear", "WorkLifeBalance", "YearsAtCompany", "YearsInCurrentRole", "YearsSinceLastPromotion", "YearsWithCurrManager")
  
  # Extract the selected columns
  train_predictors <- train[, selected_columns, drop = FALSE]
  test_predictors <- test[, selected_columns, drop = FALSE]

  train_predictors <- apply(train_predictors, 2, as.numeric)
  test_predictors <- apply(test_predictors, 2, as.numeric)
  
  train_predictors <- scale(train_predictors)
  test_predictors <- scale(test_predictors)
  
  # Convert to numeric matrices
  train_predictors <- as.matrix(train_predictors)
  test_predictors <- as.matrix(test_predictors)

  # Remove infinite values
  train_predictors[!is.finite(train_predictors)] <- 0
  test_predictors[!is.finite(test_predictors)] <- 0
  
  
if (sum(response_train == "Yes") > 0 && sum(response_test == "Yes") > 0) {
  for (i in 1:numks) {
    classifications <- knn(train_predictors, test_predictors, response_train, prob = TRUE, k = i)
    table(classifications, response_test)
    CM_AllK<- confusionMatrix(table(classifications, response_test), positive = "Yes")
    masterAcc[j, i] <- CM_AllK$overall[1]
     }
  }
}
CM_AllK
## Confusion Matrix and Statistics
## 
##                response_test
## classifications  No Yes
##             No  143  26
##             Yes   2   3
##                                           
##                Accuracy : 0.8391          
##                  95% CI : (0.7759, 0.8903)
##     No Information Rate : 0.8333          
##     P-Value [Acc > NIR] : 0.4685          
##                                           
##                   Kappa : 0.134           
##                                           
##  Mcnemar's Test P-Value : 1.383e-05       
##                                           
##             Sensitivity : 0.10345         
##             Specificity : 0.98621         
##          Pos Pred Value : 0.60000         
##          Neg Pred Value : 0.84615         
##              Prevalence : 0.16667         
##          Detection Rate : 0.01724         
##    Detection Prevalence : 0.02874         
##       Balanced Accuracy : 0.54483         
##                                           
##        'Positive' Class : Yes             
## 
MeanAcc = colMeans(masterAcc); MeanAcc
##  [1] 0.7946552 0.7893103 0.8301724 0.8294828 0.8386782 0.8394828 0.8433333
##  [8] 0.8406897 0.8425287 0.8426437
plot(seq(1, numks, 1), MeanAcc, type = "l", ylab = "Mean Accuracy (Positive Class: Yes)")

which.max(MeanAcc)
## [1] 7
max(MeanAcc)
## [1] 0.8433333

From the plot, we see that the best k is k = 7. The overall accuracy is 83.91%, but sensitivity (True Positive Rate) is low (10.35%).The model is better at correctly predicting the majority class (“No”) but struggles with the minority class (“Yes”).

Looking specifically at the Confusion Matrix statistics, this is the output and the interpretation of each of these statistics: - Sensitivity (True Positive Rate): 0.10345 The proportion of actual positives correctly predicted for those who attrited. - Specificity (True Negative Rate): 0.98621 The proportion of actual negatives correctly predicted (for those who did not leave the company) - Positive Predictive Value (Precision): 0.60000 The proportion of predicted positives that are true positives (attrited correctly identified as attrited) - Negative Predictive Value: 0.84615 The proportion of predicted negatives that are true negatives. (not attrited correctly identified as not attrited) - Prevalence: 0.16667 The proportion of actual positives in the dataset. (proportion of attrited in the overall dataset)

TRYING THRESHOLD CHANGE for KNN - All predictors; k = 7

set.seed(1234)
iterations<- 100
accuracy_table <- numeric(iterations)
trainIndices <- sample(1:dim(Attritiondata)[1], round(splitPerc * dim(Attritiondata)[1]))
accuracy_table <- numeric(iterations)  

  train <- as.data.frame(Attritiondata[trainIndices, ])
  test <- as.data.frame(Attritiondata[-trainIndices, ])

  train_features<- train[, -which(names(train) == "Attrition")]
  test_features<- test[, -which(names(test) == "Attrition")]
  
  train_target<- train$Attrition
 # train_scaled<- scale(train_features) Using this in the knn returns "No missing values allowed"
  #test_scaled<- scale(test_features)

for (i in 1:iterations) {
  classifications <- knn(train_features, test_features, train_target, prob = TRUE, k = 7)
  table(classifications, response_test)
  CM_AllK7 <- confusionMatrix(table(as.factor(test$Attrition),classifications), positive ="Yes")
  accuracy_table[i] <- CM_AllK7$overall[1]
}

#print(accuracy_table)
avg_accuracy<-mean(accuracy_table[1])
avg_accuracy
## [1] 0.7988506
specificity_table<- numeric(iterations)
sensitivity_table<- numeric(iterations)
for (i in 1:iterations) {
   classifications <- knn(train_features, test_features, train_target, prob = TRUE, k = 7)
  table(classifications, response_test)
  CM_AllK7 <- confusionMatrix(table(as.factor(test$Attrition),classifications), positive ="Yes")
  specificity_table[i] <- CM_AllK7$byClass['Specificity']
  sensitivity_table[i] <- CM_AllK7$byClass['Sensitivity']
}
CM_AllK7
## Confusion Matrix and Statistics
## 
##      classifications
##        No Yes
##   No  137   3
##   Yes  32   2
##                                           
##                Accuracy : 0.7989          
##                  95% CI : (0.7315, 0.8557)
##     No Information Rate : 0.9713          
##     P-Value [Acc > NIR] : 1               
##                                           
##                   Kappa : 0.0552          
##                                           
##  Mcnemar's Test P-Value : 2.214e-06       
##                                           
##             Sensitivity : 0.40000         
##             Specificity : 0.81065         
##          Pos Pred Value : 0.05882         
##          Neg Pred Value : 0.97857         
##              Prevalence : 0.02874         
##          Detection Rate : 0.01149         
##    Detection Prevalence : 0.19540         
##       Balanced Accuracy : 0.60533         
##                                           
##        'Positive' Class : Yes             
## 
avg_specificity<-mean(specificity_table[1])
avg_specificity
## [1] 0.8106509
avg_sensitivity<-mean(sensitivity_table[1])
avg_sensitivity
## [1] 0.4
###### New Threshold using classifications which used k = 7 from above

#classifications
#attributes(classifications) # Look at possible attributes
#attributes(classifications)$prob # Probability of what was classified for that observation

probs = ifelse(classifications == "Yes",attributes(classifications)$prob, 1- attributes(classifications)$prob)

summary(Attritiondata$Attrition)
##  No Yes 
## 730 140
140/(730+140) #16.09%
## [1] 0.1609195
NewClass = ifelse(probs > .1609, "Yes", "No")
NewClass <- factor(NewClass, levels = levels(response_test))
table(NewClass,response_test)
##         response_test
## NewClass  No Yes
##      No  115  18
##      Yes  30  11
CM_NewThreshold <- confusionMatrix(table(NewClass, response_test), positive = "Yes", mode = "everything")
CM_NewThreshold
## Confusion Matrix and Statistics
## 
##         response_test
## NewClass  No Yes
##      No  115  18
##      Yes  30  11
##                                           
##                Accuracy : 0.7241          
##                  95% CI : (0.6514, 0.7891)
##     No Information Rate : 0.8333          
##     P-Value [Acc > NIR] : 0.9999          
##                                           
##                   Kappa : 0.1479          
##                                           
##  Mcnemar's Test P-Value : 0.1124          
##                                           
##             Sensitivity : 0.37931         
##             Specificity : 0.79310         
##          Pos Pred Value : 0.26829         
##          Neg Pred Value : 0.86466         
##               Precision : 0.26829         
##                  Recall : 0.37931         
##                      F1 : 0.31429         
##              Prevalence : 0.16667         
##          Detection Rate : 0.06322         
##    Detection Prevalence : 0.23563         
##       Balanced Accuracy : 0.58621         
##                                           
##        'Positive' Class : Yes             
## 

Similar to before, the loop ran for 100 iterations, but k was set to 7 when it came to knn. There are 2 confusion matrices. We have one, without the threshold changes, and one with the threshold change. The accuracy went down with the threshold change, while sensitivity reduced by a lot, and specificity reduced by ~10%. The positive predictive value increased by 9%, and the negative pred value reduced by 14%.

The new threshold has a lower accuracy compared to the original kNN classification.Sensitivity is significantly lower for the new threshold, indicating that fewer true positives are captured.Specificity is slightly lower for the new threshold, indicating a decrease in correctly identified true negatives. Precision is lower for the new threshold, reflecting a decrease in the accuracy of positive predictions. The original KNN classification has a higher accuracy and sensitivity compared to the new threshold.

#Applying to the Test Model to predict attrition using KNN with all predictors (This is best model)

train_features<- Attritiondata[, -which(names(Attritiondata) == "Attrition")]
test_features<- AttritionTest[]#[, -which(names(AttritionTest)=="Attrition")]
#head(test_features,5)
train_target <- Attritiondata$Attrition

AttritionClassifications <- knn(train_features, test_features, train_target, prob = TRUE, k = 7)
AttritionTest$Attrition <- AttritionClassifications
#head(AttritionTest,5)

AttritionPredictionsKNN<-AttritionTest%>%select(c("ID","Attrition"))
#head(AttritionPredictionsKNN,5)
write.csv(AttritionPredictionsKNN,"CaseStudy2AttritionPredictionsKNN_RenuKarthikeyan.csv", row.names = T)

KNN Using Select Predictors

After doing my Exploratory Data Analysis, I believe the important predictors for Attrition are: Gender, Department,Job Satisfaction,Distance From Home,Monthly Income, Job Level, Age, Over Time, Percent Salary Hike, Performance Rating, and Education.

set.seed(1234)
iterations = 100
numks = 10
splitPerc = .8

masterAcc = matrix(nrow = iterations, ncol = numks)

for (j in 1:iterations) {
  trainIndices <- sample(1:dim(Attritiondata)[1], round(splitPerc * dim(Attritiondata)[1]))
  train <- as.data.frame(Attritiondata[trainIndices, ])
  test <- as.data.frame(Attritiondata[-trainIndices, ])
  
  response_train <- factor(train$Attrition)
  response_test <- factor(test$Attrition)

  #UPDATE HERE!!!!
  #train_predictors <- train[, c(2,6,7,8,13,16,18,20,24,25,26)]
  #test_predictors <- test[, c(2,6,7,8,13,16,18,20,24,25,26) ]

  selected_cols <- c(2, 6, 7, 8, 13, 16, 18, 20, 24, 25, 26)

  train_predictors <- train[, selected_cols] #subset function
  test_predictors <- test[, selected_cols]

  train_predictors <- apply(train_predictors, 2, as.numeric)
  test_predictors <- apply(test_predictors, 2, as.numeric)
  train_predictors <- scale(train_predictors)
  test_predictors <- scale(test_predictors)
  train_predictors <- as.matrix(train_predictors)
  test_predictors <- as.matrix(test_predictors)

  # Remove infinite values
  train_predictors[!is.finite(train_predictors)] <- 0
  test_predictors[!is.finite(test_predictors)] <- 0

    for (i in 1:numks) {
      classifications <- knn(train_predictors, test_predictors, response_train, prob =TRUE, k = i)
      table(classifications, response_test)
      CM_Select<- confusionMatrix(table(classifications, response_test), positive = "Yes")
      masterAcc[j, i] <- CM_Select$overall[1]
    }
}
CM_Select
## Confusion Matrix and Statistics
## 
##                response_test
## classifications  No Yes
##             No  144  24
##             Yes   4   2
##                                           
##                Accuracy : 0.8391          
##                  95% CI : (0.7759, 0.8903)
##     No Information Rate : 0.8506          
##     P-Value [Acc > NIR] : 0.7085939       
##                                           
##                   Kappa : 0.0731          
##                                           
##  Mcnemar's Test P-Value : 0.0003298       
##                                           
##             Sensitivity : 0.07692         
##             Specificity : 0.97297         
##          Pos Pred Value : 0.33333         
##          Neg Pred Value : 0.85714         
##              Prevalence : 0.14943         
##          Detection Rate : 0.01149         
##    Detection Prevalence : 0.03448         
##       Balanced Accuracy : 0.52495         
##                                           
##        'Positive' Class : Yes             
## 
MeanAcc = colMeans(masterAcc); MeanAcc
##  [1] 0.7545977 0.7523563 0.8077586 0.8095977 0.8272414 0.8263793 0.8315517
##  [8] 0.8305172 0.8338506 0.8359195
plot(seq(1, numks, 1), MeanAcc, type = "l", ylab = "Mean Accuracy (Positive Class: Yes)")

which.max(MeanAcc)
## [1] 10
max(MeanAcc)
## [1] 0.8359195

We see that the best k is k = 10. The confusion matrix is taking an average of all the k’s tried. Here, the accuracy is 83.91%, similar to the initial average confusion matrix seen for all predictors using KNN. The sensitivity is quite low at 7.69%, suggesting that the model is struggling to correctly identify positive (true Attrition) instances. The model shows high specificity (97.30%), indicating a decent ability to correctly identify negative instances (not attrition). The positive predictive value (precision) is at 33.33%, indicating that among instances predicted as positive, about one-third are true positives.

TRYING k = 10 for KNN - Select predictors

iterations<- 100
accuracy_table <- numeric(iterations)
trainIndices <- sample(1:dim(Attritiondata)[1], round(splitPerc * dim(Attritiondata)[1]))

  train <- as.data.frame(Attritiondata[trainIndices, ])
  test <- as.data.frame(Attritiondata[-trainIndices, ])

  train_features<- train[, selected_cols]
  test_features<- test[, selected_cols]
  
  train_target<- train$Attrition
  train_scaled<- scale(train_features)
  test_scaled<- scale(test_features)

for (i in 1:iterations) {
  classifications <- knn(train_features, test_features, train_target, prob = TRUE, k = 10)
  table(classifications, response_test)
  CM_SelectK <- confusionMatrix(table(as.factor(test$Attrition),classifications), positive ="Yes")
  accuracy_table[i] <- CM_SelectK$overall[1]
}

#print(accuracy_table)
avg_accuracy<-mean(accuracy_table[1]); avg_accuracy
## [1] 0.8275862
specificity_table<- numeric(iterations)
sensitivity_table<- numeric(iterations)
for (i in 1:iterations) {
   classifications <- knn(train_features, test_features, train_target, prob = TRUE, k = 10)
  table(classifications, response_test)
  CM_SelectK<- confusionMatrix(table(as.factor(test$Attrition),classifications), positive ="Yes")
  specificity_table[i] <- CM_SelectK$byClass['Specificity']
  sensitivity_table[i] <- CM_SelectK$byClass['Sensitivity']
}
CM_SelectK
## Confusion Matrix and Statistics
## 
##      classifications
##        No Yes
##   No  145   0
##   Yes  29   0
##                                           
##                Accuracy : 0.8333          
##                  95% CI : (0.7695, 0.8854)
##     No Information Rate : 1               
##     P-Value [Acc > NIR] : 1               
##                                           
##                   Kappa : 0               
##                                           
##  Mcnemar's Test P-Value : 1.999e-07       
##                                           
##             Sensitivity :     NA          
##             Specificity : 0.8333          
##          Pos Pred Value :     NA          
##          Neg Pred Value :     NA          
##              Prevalence : 0.0000          
##          Detection Rate : 0.0000          
##    Detection Prevalence : 0.1667          
##       Balanced Accuracy :     NA          
##                                           
##        'Positive' Class : Yes             
## 
avg_specificity<-mean(specificity_table[1])
avg_specificity
## [1] 0.8323699
avg_sensitivity<-mean(sensitivity_table[1])
avg_sensitivity
## [1] 0

We see the average specificity is 83.43% and sensitivity is 0%. This model’s performance is notably poor, with zero sensitivity, meaning it failed to correctly identify any positive instances. The specificity and negative predictive value are relatively high, but the lack of sensitivity indicates a serious limitation in identifying instances of the positive class. This suggests that the model might need further refinement or a different approach to address the imbalance and improve its ability to correctly classify positive instances.

Naive Bayes and Confusion Matrix - Training with All predictors

set.seed(1234)
iterations = 100

masterAcc = matrix(nrow = iterations)

splitPerc = .8 #Training / Test split Percentage

for(j in 1:iterations)
{
  trainIndices <- sample(1:dim(Attritiondata)[1], round(splitPerc * dim(Attritiondata)[1]))
  train <- as.data.frame(Attritiondata[trainIndices, ])
  test <- as.data.frame(Attritiondata[-trainIndices, ])
  
   train$Attrition <- factor(train$Attrition, levels = c("Yes", "No"))
   test$Attrition <- factor(test$Attrition, levels = c("Yes", "No"))
  
    model <- naiveBayes(train[, -3], as.factor(train$Attrition), laplace = 1)
   predictions <- predict(model, test[, -3])
   confMatrix <- table(predictions, as.factor(test$Attrition))
   CM_NB_All <- confusionMatrix(confMatrix)
   masterAcc[j] <- CM_NB_All$overall[1]
}
CM_NB_All
## Confusion Matrix and Statistics
## 
##            
## predictions Yes No
##         Yes  23 92
##         No    2 57
##                                           
##                Accuracy : 0.4598          
##                  95% CI : (0.3841, 0.5368)
##     No Information Rate : 0.8563          
##     P-Value [Acc > NIR] : 1               
##                                           
##                   Kappa : 0.1211          
##                                           
##  Mcnemar's Test P-Value : <2e-16          
##                                           
##             Sensitivity : 0.9200          
##             Specificity : 0.3826          
##          Pos Pred Value : 0.2000          
##          Neg Pred Value : 0.9661          
##              Prevalence : 0.1437          
##          Detection Rate : 0.1322          
##    Detection Prevalence : 0.6609          
##       Balanced Accuracy : 0.6513          
##                                           
##        'Positive' Class : Yes             
## 
MeanAcc = colMeans(masterAcc); MeanAcc
## [1] 0.6482184

Given all the predictors, the sensitivity rate of the model is the percentage of actual attrition cases correctly identified. It measures the model’s ability to capture employees who are truly at risk of attrition among all employees who actually attrite. This model shows imbalanced performance with high sensitivity (high attrition) but low specificity. It performs well in identifying actual positive instances (attrition) but struggles to correctly identify negative instances(no attrition). The positive predictive value is relatively low, indicating that when it predicts a positive instance, it has a 20% chance of being correct.

Naive Bayes and Confusion Matrix - Training; Using Select predictors to determine Attrition

set.seed(1234)
iterations = 100

masterAcc = matrix(nrow = iterations)

splitPerc = .8 #Training / Test split Percentage

for(j in 1:iterations)
{
  trainIndices <- sample(1:dim(Attritiondata)[1], round(splitPerc * dim(Attritiondata)[1]))
  train <- as.data.frame(Attritiondata[trainIndices, ])
  test <- as.data.frame(Attritiondata[-trainIndices, ])
 
   train$Attrition <- factor(train$Attrition, levels = c("Yes", "No"))
   test$Attrition <- factor(test$Attrition, levels = c("Yes", "No"))
  
  model2 <- naiveBayes(train[, c(2, 6, 7, 8, 13, 16, 18, 20, 24, 25, 26)], as.factor(train$Attrition), laplace = 1)
  predictions <- predict(model2, test[, c(2, 6, 7, 8, 13, 16, 18, 20, 24, 25, 26)])
   confMatrix <- table(predictions, as.factor(test$Attrition))
   CM_NB_Select <- confusionMatrix(confMatrix)
   masterAcc[j] <- CM_NB_Select$overall[1]
}
CM_NB_Select
## Confusion Matrix and Statistics
## 
##            
## predictions Yes  No
##         Yes   3   4
##         No   22 145
##                                        
##                Accuracy : 0.8506       
##                  95% CI : (0.7888, 0.9)
##     No Information Rate : 0.8563       
##     P-Value [Acc > NIR] : 0.6357048    
##                                        
##                   Kappa : 0.133        
##                                        
##  Mcnemar's Test P-Value : 0.0008561    
##                                        
##             Sensitivity : 0.12000      
##             Specificity : 0.97315      
##          Pos Pred Value : 0.42857      
##          Neg Pred Value : 0.86826      
##              Prevalence : 0.14368      
##          Detection Rate : 0.01724      
##    Detection Prevalence : 0.04023      
##       Balanced Accuracy : 0.54658      
##                                        
##        'Positive' Class : Yes          
## 
MeanAcc = colMeans(masterAcc)

MeanAcc
## [1] 0.8312069
#use predict function on the "validation" sets. Use the same model. Test will be validation set. 
Predictions<- predict(model2,AttritionTest[,c(2, 5, 6, 7, 12, 15, 17, 19, 23, 24, 25)])

AttritionTest$Attrition<- Predictions
#View(AttritionTest$Attrition)

AttritionPredictionsNB<- AttritionTest %>% select(c("ID","Attrition"))
write.csv(AttritionPredictionsNB,"CaseStudy2AttritionPredictionsNB_RenuKarthikeyan.csv", row.names = T)

Sensitivity is 12%; 12% of actual attrition cases are correctly identified by the model. This suggests that the model may not be very effective at capturing employees who are truly at risk of attrition. This model has a higher accuracy of 85.06%, and has imbalanced performance with low sensitivity and high specificity. However, accuracy can be misleading, especially in imbalanced datasets where one class (e.g., “No attrition”) dominates. In this case, accuracy is not the best metric to evaluate the model’s performance. Positive predictive value (PPV) is at 42.86%. This indicates that when the model predicts attrition, there’s a 42.86% chance that the prediction is correct. It reflects the precision of the model in identifying true positive cases among all instances predicted as positive. The low prevalence (the proportion of actual positive cases in the dataset) of attrition, is 14.37%. This low prevalence contributes to the imbalanced nature of the performance metrics.

Best Model Determination from the Models tried for Attrition (KNN and Naive Bayes)

It looks like the KNN model at k = 7 with all predictors without threshold adjustment has better accuracy within the KNN models. The Naive Bayes model with select predictors has the highest accuracy, and is better than the other Naive Bayes model which included all predictors.

Naive Bayes has a higher accuracy (85.06%) compared to KNN (79.89%). However, accuracy alone may not be the most informative metric, especially in imbalanced datasets.KNN has a higher sensitivity (40.00%) compared to Naive Bayes (12.00%). Sensitivity is crucial when identifying cases of attrition, as it represents the proportion of true positive cases among all actual positive cases.Naive Bayes has higher specificity (97.32%) compared to KNN (81.07%). Specificity is important when minimizing false positives, but it’s essential to balance it with sensitivity.Naïve Bayes has a higher positive predictive value (precision) at 42.86%, while KNN has a lower precision at 5.88%. Precision indicates the accuracy of positive predictions.

Of the 2 best models (best in KNN and best in Naive Bayes), I think the Naive Bayes is the better model to predict Attrition, given the high positive prediction value(precision), accuracy, and narrower confidence interval.

Thank You

This concludes this presentation and analysis. Thank you for your time and I look forward to empowering Frito Lay with data-driven wisdom. I created a shiny app to visualize and notice insights regarding the attrition data. Please feel free to look into the link provided. If you have any questions, please feel free to reach out to me, my email is in the attached PowerPoint presentation. Thank you!